R/descriptives_function.R
In MattiaGirardi1997/Understanding-Complex-Networks:
Defines functions
index.boxplots
index.scatterplots
plot.nodes.and.edges
#########################################
## Descriptives
## Mattia Girardi
## 15.01.2021
########################################
#' Plot nodes & edges
#'
#' @param measures network measures
#' @return plot; x-axis: nodes, y-axis: edges
#' @export
#' @import data.table, igraph, dplyr
plot.nodes.and.edges <- function(measures){
ggplot(measures, aes(x = Nodes, y = Edges, color = NetworkDomain)) +
geom_point(size = 3) + scale_x_log10() + scale_y_log10(labels = function(x) format(x, scientific = FALSE)) +
scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Edges*") + xlab("Nodes*") + labs(color = "Network Domain") + theme(panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 1),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 25),
axis.title.x = element_text(size = 25),
axis.text.x = element_text(size = 20, colour = "Black", angle = 45, hjust = 1),
axis.text.y = element_text(size = 20, colour = "Black", angle = 45, hjust = 1),
legend.key.height = unit(1, "cm"),
legend.key.width = unit(1, "cm"),
legend.position = c(0.8, 0.25),
legend.background = element_rect(size = 0.1, colour = "Black"),
legend.key = element_blank(),
legend.text = element_text(size = 20),
legend.title = element_text(size = 20)) +
guides(colour = guide_legend(override.aes = list(size=5)))
}
#' Create scatterplots
#'
#' @param measures network measures
#' @return scatterplots; x-axis: nodes, y-axis: measures
#' @export
#' @import data.table, igraph, dplyr
index.scatterplots <- function(measures){
a <- ggplot(measures, aes(x = Nodes, y = AveragePathLength, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Path Length*") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Assortativity
b <- ggplot(measures, aes(x = Nodes, y = DegreeAssortativity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Assortativity") + ylim(-1,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Density
c <- ggplot(measures, aes(x = Nodes, y = Density, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Density") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Degree
d <- ggplot(measures, aes(x = Nodes, y = AverageDegree, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Degree*") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Median Degree
e <- ggplot(measures, aes(x = Nodes, y = MedianDegree, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Median Degree*") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Transitivity
f <- ggplot(measures, aes(x = Nodes, y = AverageTransitivity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Transitivity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Global Transivity
g <- ggplot(measures, aes(x = Nodes, y = GlobalTransitivity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Global Transitivity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Transitivity
h <- ggplot(measures, aes(x = Nodes, y = GiniTransitivity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Transitivity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Betweenness Centrality
i <- ggplot(measures, aes(x = Nodes, y = BetweennessCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Betweenness Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Closeness Centrality
j <- ggplot(measures, aes(x = Nodes, y = ClosenessCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Closeness Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Centrality
k <- ggplot(measures, aes(x = Nodes, y = DegreeCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Eigenvector Centrality
l <- ggplot(measures, aes(x = Nodes, y = EigenvectorCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Eigenvector Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Betweenness
m <- ggplot(measures, aes(x = Nodes, y = GiniBetweenness, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Betweenness") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Closeness
n <- ggplot(measures, aes(x = Nodes, y = GiniCloseness, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Closeness") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Degree Distribution
o <- ggplot(measures, aes(x = Nodes, y = GiniDegreeDistribution, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Degree Distribution") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Eigenvector Centrality
p <- ggplot(measures, aes(x = Nodes, y = GiniEigenvectorCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Eigenvector Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Complexity
q <- ggplot(measures, aes(x = Nodes, y = Complexity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Complexity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Entropy
r <- ggplot(measures, aes(x = Nodes, y = Entropy, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Entropy") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
#### legend plot
s <- as_ggplot(get_legend(ggplot(measures, aes(x = NetworkDomain, y = EigenvectorCentrality, color = NetworkDomain)) +
geom_point() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Eigenvector Centrality") + ylim(0,1) + xlab("") + labs(color = "Network Domain") +
theme(legend.key.size = unit(1, "cm"),
legend.text = element_text(size = 10),
legend.title = element_text(size = 15))
))
grid.arrange(a, b, c, d, e, f, i, j, k, l, g, m, n, o, p, h, q, r, s, nrow = 4, ncol = 5)
}
#' Create boxplots
#'
#' @param measures network measures
#' @return boxplots; x-axis: nodes, y-axis: measures
#' @export
#' @import data.table, igraph, dplyr
index.boxplots <- function(measures){
a <- ggplot(measures, aes(x = NetworkDomain, y = AveragePathLength, color = NetworkDomain)) +
geom_boxplot() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Path Length*") + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Assortativity
b <- ggplot(measures, aes(x = NetworkDomain, y = DegreeAssortativity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Assortativity") + ylim(-1,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Density
c <- ggplot(measures, aes(x = NetworkDomain, y = Density, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Density") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Degree
d <- ggplot(measures, aes(x = NetworkDomain, y = AverageDegree, color = NetworkDomain)) +
geom_boxplot() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Degree*") + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Median Degree
e <- ggplot(measures, aes(x = NetworkDomain, y = MedianDegree, color = NetworkDomain)) +
geom_boxplot() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Median Degree*") + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Global Transivity
f <- ggplot(measures, aes(x = NetworkDomain, y = GlobalTransitivity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Global Transitivity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Transitivity
g <- ggplot(measures, aes(x = NetworkDomain, y = GiniTransitivity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Transitivity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Transitivity
h <- ggplot(measures, aes(x = NetworkDomain, y = AverageTransitivity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Transitivity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Betweenness Centrality
i <- ggplot(measures, aes(x = NetworkDomain, y = BetweennessCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Betweenness Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Closeness Centrality
j <- ggplot(measures, aes(x = NetworkDomain, y = ClosenessCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Closeness Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Centrality
k <- ggplot(measures, aes(x = NetworkDomain, y = DegreeCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Eigenvector Centrality
l <- ggplot(measures, aes(x = NetworkDomain, y = EigenvectorCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Eigenvector Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Betweenness
m <- ggplot(measures, aes(x = NetworkDomain, y = GiniBetweenness, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Betweenness") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Closeness
n <- ggplot(measures, aes(x = NetworkDomain, y = GiniCloseness, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Closeness") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Degree Distribution
o <- ggplot(measures, aes(x = NetworkDomain, y = GiniDegreeDistribution, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Degree Distribution") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Eigenvector Centrality
p <- ggplot(measures, aes(x = NetworkDomain, y = GiniEigenvectorCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Eigenvector Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Complexity
q <- ggplot(measures, aes(x = NetworkDomain, y = Complexity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Complexity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Entropy
r <- ggplot(measures, aes(x = NetworkDomain, y = Entropy, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Entropy") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
grid.arrange(a, b, c, d, e, f, i, j, k, l, g, m, n, o, p, h, q, r, nrow = 4, ncol = 5)
}
MattiaGirardi1997/Understanding-Complex-Networks documentation built on Feb. 26, 2021, 12:23 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions index.boxplots index.scatterplots plot.nodes.and.edges
#########################################
## Descriptives
## Mattia Girardi
## 15.01.2021
########################################
#' Plot nodes & edges
#'
#' @param measures network measures
#' @return plot; x-axis: nodes, y-axis: edges
#' @export
#' @import data.table, igraph, dplyr
plot.nodes.and.edges <- function(measures){
ggplot(measures, aes(x = Nodes, y = Edges, color = NetworkDomain)) +
geom_point(size = 3) + scale_x_log10() + scale_y_log10(labels = function(x) format(x, scientific = FALSE)) +
scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Edges*") + xlab("Nodes*") + labs(color = "Network Domain") + theme(panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 1),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 25),
axis.title.x = element_text(size = 25),
axis.text.x = element_text(size = 20, colour = "Black", angle = 45, hjust = 1),
axis.text.y = element_text(size = 20, colour = "Black", angle = 45, hjust = 1),
legend.key.height = unit(1, "cm"),
legend.key.width = unit(1, "cm"),
legend.position = c(0.8, 0.25),
legend.background = element_rect(size = 0.1, colour = "Black"),
legend.key = element_blank(),
legend.text = element_text(size = 20),
legend.title = element_text(size = 20)) +
guides(colour = guide_legend(override.aes = list(size=5)))
}
#' Create scatterplots
#'
#' @param measures network measures
#' @return scatterplots; x-axis: nodes, y-axis: measures
#' @export
#' @import data.table, igraph, dplyr
index.scatterplots <- function(measures){
a <- ggplot(measures, aes(x = Nodes, y = AveragePathLength, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Path Length*") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Assortativity
b <- ggplot(measures, aes(x = Nodes, y = DegreeAssortativity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Assortativity") + ylim(-1,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Density
c <- ggplot(measures, aes(x = Nodes, y = Density, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Density") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Degree
d <- ggplot(measures, aes(x = Nodes, y = AverageDegree, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Degree*") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Median Degree
e <- ggplot(measures, aes(x = Nodes, y = MedianDegree, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Median Degree*") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Transitivity
f <- ggplot(measures, aes(x = Nodes, y = AverageTransitivity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Transitivity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Global Transivity
g <- ggplot(measures, aes(x = Nodes, y = GlobalTransitivity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Global Transitivity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Transitivity
h <- ggplot(measures, aes(x = Nodes, y = GiniTransitivity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Transitivity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Betweenness Centrality
i <- ggplot(measures, aes(x = Nodes, y = BetweennessCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Betweenness Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Closeness Centrality
j <- ggplot(measures, aes(x = Nodes, y = ClosenessCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Closeness Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Centrality
k <- ggplot(measures, aes(x = Nodes, y = DegreeCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Eigenvector Centrality
l <- ggplot(measures, aes(x = Nodes, y = EigenvectorCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Eigenvector Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Betweenness
m <- ggplot(measures, aes(x = Nodes, y = GiniBetweenness, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Betweenness") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Closeness
n <- ggplot(measures, aes(x = Nodes, y = GiniCloseness, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Closeness") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Degree Distribution
o <- ggplot(measures, aes(x = Nodes, y = GiniDegreeDistribution, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Degree Distribution") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Eigenvector Centrality
p <- ggplot(measures, aes(x = Nodes, y = GiniEigenvectorCentrality, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Eigenvector Centrality") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Complexity
q <- ggplot(measures, aes(x = Nodes, y = Complexity, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Complexity") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Entropy
r <- ggplot(measures, aes(x = Nodes, y = Entropy, color = NetworkDomain)) +
geom_point(size = 0.6) + scale_x_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Entropy") + ylim(0,1) + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 7),
axis.title.x = element_blank(),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
#### legend plot
s <- as_ggplot(get_legend(ggplot(measures, aes(x = NetworkDomain, y = EigenvectorCentrality, color = NetworkDomain)) +
geom_point() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Eigenvector Centrality") + ylim(0,1) + xlab("") + labs(color = "Network Domain") +
theme(legend.key.size = unit(1, "cm"),
legend.text = element_text(size = 10),
legend.title = element_text(size = 15))
))
grid.arrange(a, b, c, d, e, f, i, j, k, l, g, m, n, o, p, h, q, r, s, nrow = 4, ncol = 5)
}
#' Create boxplots
#'
#' @param measures network measures
#' @return boxplots; x-axis: nodes, y-axis: measures
#' @export
#' @import data.table, igraph, dplyr
index.boxplots <- function(measures){
a <- ggplot(measures, aes(x = NetworkDomain, y = AveragePathLength, color = NetworkDomain)) +
geom_boxplot() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Path Length*") + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Assortativity
b <- ggplot(measures, aes(x = NetworkDomain, y = DegreeAssortativity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Assortativity") + ylim(-1,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Density
c <- ggplot(measures, aes(x = NetworkDomain, y = Density, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Density") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Degree
d <- ggplot(measures, aes(x = NetworkDomain, y = AverageDegree, color = NetworkDomain)) +
geom_boxplot() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Degree*") + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Median Degree
e <- ggplot(measures, aes(x = NetworkDomain, y = MedianDegree, color = NetworkDomain)) +
geom_boxplot() + scale_y_log10() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Median Degree*") + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Global Transivity
f <- ggplot(measures, aes(x = NetworkDomain, y = GlobalTransitivity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Global Transitivity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Transitivity
g <- ggplot(measures, aes(x = NetworkDomain, y = GiniTransitivity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Transitivity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Average Transitivity
h <- ggplot(measures, aes(x = NetworkDomain, y = AverageTransitivity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Average Transitivity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Betweenness Centrality
i <- ggplot(measures, aes(x = NetworkDomain, y = BetweennessCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Betweenness Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Closeness Centrality
j <- ggplot(measures, aes(x = NetworkDomain, y = ClosenessCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Closeness Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Degree Centrality
k <- ggplot(measures, aes(x = NetworkDomain, y = DegreeCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Degree Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Eigenvector Centrality
l <- ggplot(measures, aes(x = NetworkDomain, y = EigenvectorCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Eigenvector Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Betweenness
m <- ggplot(measures, aes(x = NetworkDomain, y = GiniBetweenness, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Betweenness") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Closeness
n <- ggplot(measures, aes(x = NetworkDomain, y = GiniCloseness, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Closeness") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Degree Distribution
o <- ggplot(measures, aes(x = NetworkDomain, y = GiniDegreeDistribution, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Degree Distribution") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Gini Eigenvector Centrality
p <- ggplot(measures, aes(x = NetworkDomain, y = GiniEigenvectorCentrality, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Gini Eigenvector Centrality") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Complexity
q <- ggplot(measures, aes(x = NetworkDomain, y = Complexity, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Complexity") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
### Entropy
r <- ggplot(measures, aes(x = NetworkDomain, y = Entropy, color = NetworkDomain)) +
geom_boxplot() + scale_color_manual(values = c("gray20", "orangered1", "dodgerblue1")) +
ylab("Entropy") + ylim(0,1) + xlab("") + theme(legend.position = "none",
panel.background = element_blank(),
panel.grid.major = element_line(colour = "gray85", size = 0.5),
panel.grid.minor = element_line(colour = "gray85"),
axis.ticks = element_blank(),
axis.title.y = element_text(size = 9),
axis.text.x = element_text(size = 6, colour = "Black", angle = 45, hjust = 1))
grid.arrange(a, b, c, d, e, f, i, j, k, l, g, m, n, o, p, h, q, r, nrow = 4, ncol = 5)
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.