R/plot_DT.R
In CedricMondy/ecodiag: Build Standardized Diagnostic Tool Models
#' Plot the predictions of a DT model
#'
#' This function is a wrapper around the
#' [ggradar](https://github.com/ricardo-bion/ggradar/blob/master/R/ggradar.R)
#' function and produces radar plot for the DT model predictions.
#'
#' @param plot.data dataframe comprising samples in rows and DT model
#' predictions in columns (as returned by [run_DT][run_DT])
#' @param axis.labels names of axis labels if other than column names supplied
#' via plot.data
#' @param grid.line.width,gridline.min.colour,gridline.mid.colour,gridline.max.colour
#' controls for the appearance of some aspects the 'minimum', 'average' and
#' 'maximum' grid lines.
#' @param axis.label.offset vertical displacement of axis labels from maximum
#' grid line, measured relative to circle diameter
#' @param axis.line.colour colour of the axes
#' @param axis.label.size,grid.label.size,legend.text.size text size
#' @param group.line.width,group.point.size controls for the appearance of some
#' aspects of the sample lines
#' @param background.circle.colour,background.circle.transparency controls for
#' the appearance of background circle
#' @param plot.legend logical, does the legend be printed or not
#' @param legend.title,plot.title titles
#' @param byRow logical, should one radar plot be returned for each sample ID
#'
#'
#' @references script adapted from
#' https://github.com/ricardo-bion/ggradar/blob/master/R/ggradar.R
#'
#' @importFrom dplyr "%>%"
#' @export
plot_DT <- function(plot.data,
axis.labels = colnames(plot.data)[-1],
grid.line.width = 0.5,
gridline.min.colour = "grey",
gridline.mid.colour = "#007A87",
gridline.max.colour = "grey",
grid.label.size = 7,
axis.label.offset = 1.15,
axis.label.size = 8,
axis.line.colour = "grey",
group.line.width = 1.5,
group.point.size = 6,
background.circle.colour = "#D7D6D1",
background.circle.transparency = 0.2,
plot.legend = if (nrow(plot.data) > 1) TRUE else FALSE,
legend.title = "",
plot.title = "",
legend.text.size = grid.label.size,
byRow = FALSE) {
ID <- x <- y <- text <- axis.no <- NULL
if (byRow) {
IDs <- plot.data$ID
plotList <- lapply(IDs,
function(i) {
subset(plot.data, ID == i)
}) %>%
lapply(function(x) {
plot_DT(plot.data = x,
axis.labels = axis.labels,
grid.line.width = grid.line.width,
gridline.min.colour = gridline.min.colour,
gridline.mid.colour = gridline.mid.colour,
gridline.max.colour = gridline.max.colour,
grid.label.size = grid.label.size,
axis.label.offset = axis.label.offset,
axis.label.size = axis.label.size,
axis.line.colour = axis.line.colour,
group.line.width = group.line.width,
group.point.size = group.point.size,
background.circle.colour = background.circle.colour,
background.circle.transparency = background.circle.transparency,
plot.legend = FALSE,
legend.title = "",
plot.title = "",
legend.text.size = legend.text.size,
byRow = FALSE)})
names(plotList) <- IDs
return(plotList)
} else {
values.radar <- c("0.0", "0.5", "1.0")
grid.min <- 0
grid.mid <- 0.5
grid.max <- 1
centre.y <- grid.min - ((1/9)*(grid.max - grid.min))
plot.extent.x.sf <- 1
plot.extent.y.sf <- 1.2
x.centre.range <- 0.02*(grid.max - centre.y)
gridline.label.offset <- -0.1*(grid.max - centre.y)
gridline.min.linetype <- "longdash"
gridline.mid.linetype <- "longdash"
gridline.max.linetype <- "longdash"
plot.data <- as.data.frame(plot.data)
plot.data.min <- plot.data.max <- NULL
plot.data[,1] <- as.factor(as.character(plot.data[,1]))
names(plot.data)[1] <- "group"
var.names <- colnames(plot.data)[-1] #'Short version of variable names
#axis.labels [if supplied] is designed to hold 'long version' of variable
#names with line-breaks indicated using \n
#caclulate total plot extent as radius of outer circle x a user-specifiable
#scaling factor
plot.extent.x <- (grid.max + abs(centre.y))*plot.extent.x.sf
plot.extent.y <- (grid.max + abs(centre.y))*plot.extent.y.sf
#Check supplied data makes sense
if (length(axis.labels) != ncol(plot.data) - 1)
stop("'axis.labels' contains the wrong number of axis labels")
if (min(plot.data[,-1]) < centre.y)
stop("plot.data' contains value(s) < centre.y")
if (max(plot.data[,-1]) > grid.max)
stop("'plot.data' contains value(s) > grid.max")
#Declare required internal functions
CalculateGroupPath <- function(df) {
#Converts variable values into a set of radial x-y coordinates
#Code adapted from a solution posted by Tony M to
#http://stackoverflow.com/questions/9614433/creating-radar-chart-a-k-a-star-plot-spider-plot-using-ggplot2-in-r
#Args:
# df: Col 1 - group ('unique' cluster / group ID of entity)
# Col 2-n: v1.value to vn.value - values (e.g. group/cluser mean or
# median) of variables v1 to v.n
path <- as.factor(df[,1])
##find increment
angles <- seq(from = 0, to = 2*pi, by = (2*pi)/(ncol(df) - 1))
##create graph data frame
graphData <- data.frame(seg = "", x = 0, y = 0)
graphData <- graphData[-1,]
for (i in levels(path)) {
pathData <- subset(df, df[,1] == i)
for (j in c(2:ncol(df))) {
#pathData[,j]= pathData[,j]
graphData <- rbind(graphData,
data.frame(group = i,
x = pathData[,j]*sin(angles[j - 1]),
y = pathData[,j]*cos(angles[j - 1])))
}
##complete the path by repeating first pair of coords in the path
graphData <- rbind(graphData,
data.frame(group = i,
x = pathData[,2]*sin(angles[1]),
y = pathData[,2]*cos(angles[1])))
}
#Make sure that name of first column matches that of input data (in case
#!="group")
colnames(graphData)[1] <- colnames(df)[1]
graphData #data frame returned by function
}
CaclulateAxisPath <- function(var.names,min,max) {
#Caculates x-y coordinates for a set of radial axes (one per variable
#being plotted in radar plot)
#Args:
#var.names - list of variables to be plotted on radar plot
#min - MININUM value required for the plotted axes (same value will be
#applied to all axes)
#max - MAXIMUM value required for the plotted axes (same value will be
#applied to all axes)
#var.names <- c("v1","v2","v3","v4","v5")
n.vars <- length(var.names) # number of vars (axes) required
#Cacluate required number of angles (in radians)
angles <- seq(from = 0, to = 2*pi, by = (2*pi)/n.vars)
#calculate vectors of min and max x+y coords
min.x <- min*sin(angles)
min.y <- min*cos(angles)
max.x <- max*sin(angles)
max.y <- max*cos(angles)
#Combine into a set of uniquely numbered paths (one per variable)
axisData <- NULL
for (i in 1:n.vars) {
a <- c(i,min.x[i],min.y[i])
b <- c(i,max.x[i],max.y[i])
axisData <- rbind(axisData, a, b)
}
#Add column names + set row names = row no. to allow conversion into a
#data frame
colnames(axisData) <- c("axis.no","x","y")
rownames(axisData) <- seq(1:nrow(axisData))
#Return calculated axis paths
as.data.frame(axisData)
}
funcCircleCoords <- function(center = c(0,0), r = 1, npoints = 100){
#Adapted from Joran's response to
#http://stackoverflow.com/questions/6862742/draw-a-circle-with-ggplot2
tt <- seq(0,2*pi,length.out = npoints)
xx <- center[1] + r * cos(tt)
yy <- center[2] + r * sin(tt)
return(data.frame(x = xx, y = yy))
}
### Convert supplied data into plottable format
#(a) add abs(centre.y) to supplied plot data [creates plot centroid of 0,0
#for internal use, regardless of min. value of y in user-supplied data]
plot.data.offset <- plot.data
plot.data.offset[,2:ncol(plot.data.offset)] <-
plot.data[,2:ncol(plot.data)] + abs(centre.y)
#print(plot.data.offset)
# (b) convert into radial coords
group <- NULL
group$path <- CalculateGroupPath(plot.data.offset)
#print(group$path)
# (c) Calculate coordinates required to plot radial variable axes
axis <- NULL
axis$path <- CaclulateAxisPath(var.names,
grid.min + abs(centre.y),
grid.max + abs(centre.y))
#print(axis$path)
# (d) Create file containing axis labels + associated plotting coordinates
#Labels
axis$label <- data.frame(
text = axis.labels,
x = NA,
y = NA )
#print(axis$label)
#axis label coordinates
n.vars <- length(var.names)
angles <- seq(from = 0, to = 2*pi, by = (2*pi)/n.vars)
axis$label$x <- sapply(1:n.vars,
function(i, x) {
((grid.max + abs(centre.y))*axis.label.offset)*sin(angles[i])
})
axis$label$y <- sapply(1:n.vars,
function(i, x) {
((grid.max + abs(centre.y))*axis.label.offset)*cos(angles[i])
})
#print(axis$label)
# (e) Create Circular grid-lines + labels
#caclulate the coordinates required to plot circular grid-lines for three
#user-specified
#y-axis values: min, mid and max [grid.min; grid.mid; grid.max]
gridline <- NULL
gridline$min$path <- funcCircleCoords(c(0,0),
grid.min + abs(centre.y),
npoints = 360)
gridline$mid$path <- funcCircleCoords(c(0,0),
grid.mid + abs(centre.y),
npoints = 360)
gridline$max$path <- funcCircleCoords(c(0,0),
grid.max + abs(centre.y),
npoints = 360)
#print(head(gridline$max$path))
#gridline labels
gridline$min$label <- data.frame(x = gridline.label.offset,
y = grid.min + abs(centre.y),
text = as.character(grid.min))
gridline$max$label <- data.frame(x = gridline.label.offset,
y = grid.max + abs(centre.y),
text = as.character(grid.max))
gridline$mid$label <- data.frame(x = gridline.label.offset,
y = grid.mid + abs(centre.y),
text = as.character(grid.mid))
#print(gridline$min$label)
#print(gridline$max$label)
#print(gridline$mid$label)
### Start building up the radar plot
# Declare 'theme_clear', with or without a plot legend as required by user
#[default = no legend if only 1 group [path] being plotted]
theme_clear <- ggplot2::theme_bw(base_size = 20) +
ggplot2::theme(axis.text.y = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.border = ggplot2::element_blank(),
legend.key = ggplot2::element_rect(linetype = "blank"))
#Base-layer = axis labels + plot extent
# [need to declare plot extent as well, since the axis labels don't always
# fit within the plot area automatically calculated by ggplot, even if all
# included in first plot; and in any case the strategy followed here is to
# first plot right-justified labels for axis labels to left of Y axis for x<
# (-x.centre.range)], then centred labels for axis labels almost immediately
# above/below x= 0 [abs(x) < x.centre.range]; then left-justified axis
# labels to right of Y axis [x>0]. This building up the plot in layers
# doesn't allow ggplot to correctly identify plot extent when plotting first
# (base) layer]
#base layer = axis labels for axes to left of central y-axis [x< -(x.centre.range)]
base <- ggplot2::ggplot(axis$label) +
ggplot2::xlab(NULL) +
ggplot2::ylab(NULL) +
ggplot2::coord_equal() +
ggplot2::geom_text(data = subset(axis$label,axis$label$x < (-x.centre.range)),
ggplot2::aes(x = x, y = y, label = text),
size = axis.label.size, hjust = 1) +
ggplot2::scale_x_continuous(limits = c(-1.5*plot.extent.x,
1.5*plot.extent.x)) +
ggplot2::scale_y_continuous(limits = c(-plot.extent.y,
plot.extent.y)) +
ggplot2::geom_text(data = subset(axis$label,
abs(axis$label$x) <= x.centre.range),
ggplot2::aes(x = x, y = y, label = text),
size = axis.label.size, hjust = 0.5) +
ggplot2::geom_text(data = subset(axis$label,
axis$label$x > x.centre.range),
ggplot2::aes(x = x, y = y, label = text),
size = axis.label.size, hjust = 0) +
ggplot2::labs(colour = legend.title,
size = legend.text.size) +
ggplot2::geom_polygon(data = gridline$max$path,
ggplot2::aes(x,y),
fill = background.circle.colour,
alpha = background.circle.transparency) +
ggplot2::geom_path(data = axis$path,
ggplot2::aes(x = x, y = y,
group = axis.no),
colour = axis.line.colour)
base <- base +
ggplot2::geom_path(data = group$path,
ggplot2::aes(x = x, y = y,
group = group, colour = group),
size = group.line.width) +
ggplot2::geom_point(data = group$path,
ggplot2::aes(x = x, y = y,
group = group, colour = group),
size = group.point.size) +
ggplot2::geom_path(data = gridline$min$path,
ggplot2::aes(x = x, y = y),
lty = gridline.min.linetype,
colour = gridline.min.colour,
size = grid.line.width) +
ggplot2::geom_path(data = gridline$mid$path,
ggplot2::aes(x = x, y = y),
lty = gridline.mid.linetype,
colour = gridline.mid.colour,
size = grid.line.width) +
ggplot2::geom_path(data = gridline$max$path,
ggplot2::aes(x = x, y = y),
lty = gridline.max.linetype,
colour = gridline.max.colour,
size = grid.line.width) +
ggplot2::geom_text(data = gridline$min$label,
ggplot2::aes(x = x, y = y,
label = values.radar[1]),
size = grid.label.size*0.8,
hjust = 1) +
ggplot2::geom_text(data = gridline$mid$label,
ggplot2::aes(x = x, y = y,
label = values.radar[2]),
size = grid.label.size*0.8,
hjust = 1) +
ggplot2::geom_text(data = gridline$max$label,
ggplot2::aes(x = x, y = y,
label = values.radar[3]),
size = grid.label.size*0.8,
hjust = 1) +
theme_clear +
ggplot2::theme(legend.key.width = ggplot2::unit(3,"line")) +
ggplot2::theme(text = ggplot2::element_text(size = 20)) +
ggplot2::theme(legend.text = ggplot2::element_text(size = legend.text.size),
legend.position = "left") +
ggplot2::theme(legend.key.height = ggplot2::unit(2,"line")) +
ggplot2::scale_colour_manual(values =
rep(c("#FF5A5F", "#FFB400",
"#007A87", "#8CE071",
"#7B0051", "#00D1C1",
"#FFAA91", "#B4A76C",
"#9CA299", "#565A5C",
"#00A04B", "#E54C20"),
100))
if (!plot.legend) {
base <- base +
ggplot2::theme(legend.position = "none")
}
if (plot.title != "") {
base <- base +
ggplot2::ggtitle(plot.title)
}
return(base)
}
}
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#' Plot the predictions of a DT model
#'
#' This function is a wrapper around the
#' [ggradar](https://github.com/ricardo-bion/ggradar/blob/master/R/ggradar.R)
#' function and produces radar plot for the DT model predictions.
#'
#' @param plot.data dataframe comprising samples in rows and DT model
#' predictions in columns (as returned by [run_DT][run_DT])
#' @param axis.labels names of axis labels if other than column names supplied
#' via plot.data
#' @param grid.line.width,gridline.min.colour,gridline.mid.colour,gridline.max.colour
#' controls for the appearance of some aspects the 'minimum', 'average' and
#' 'maximum' grid lines.
#' @param axis.label.offset vertical displacement of axis labels from maximum
#' grid line, measured relative to circle diameter
#' @param axis.line.colour colour of the axes
#' @param axis.label.size,grid.label.size,legend.text.size text size
#' @param group.line.width,group.point.size controls for the appearance of some
#' aspects of the sample lines
#' @param background.circle.colour,background.circle.transparency controls for
#' the appearance of background circle
#' @param plot.legend logical, does the legend be printed or not
#' @param legend.title,plot.title titles
#' @param byRow logical, should one radar plot be returned for each sample ID
#'
#'
#' @references script adapted from
#' https://github.com/ricardo-bion/ggradar/blob/master/R/ggradar.R
#'
#' @importFrom dplyr "%>%"
#' @export
plot_DT <- function(plot.data,
axis.labels = colnames(plot.data)[-1],
grid.line.width = 0.5,
gridline.min.colour = "grey",
gridline.mid.colour = "#007A87",
gridline.max.colour = "grey",
grid.label.size = 7,
axis.label.offset = 1.15,
axis.label.size = 8,
axis.line.colour = "grey",
group.line.width = 1.5,
group.point.size = 6,
background.circle.colour = "#D7D6D1",
background.circle.transparency = 0.2,
plot.legend = if (nrow(plot.data) > 1) TRUE else FALSE,
legend.title = "",
plot.title = "",
legend.text.size = grid.label.size,
byRow = FALSE) {
ID <- x <- y <- text <- axis.no <- NULL
if (byRow) {
IDs <- plot.data$ID
plotList <- lapply(IDs,
function(i) {
subset(plot.data, ID == i)
}) %>%
lapply(function(x) {
plot_DT(plot.data = x,
axis.labels = axis.labels,
grid.line.width = grid.line.width,
gridline.min.colour = gridline.min.colour,
gridline.mid.colour = gridline.mid.colour,
gridline.max.colour = gridline.max.colour,
grid.label.size = grid.label.size,
axis.label.offset = axis.label.offset,
axis.label.size = axis.label.size,
axis.line.colour = axis.line.colour,
group.line.width = group.line.width,
group.point.size = group.point.size,
background.circle.colour = background.circle.colour,
background.circle.transparency = background.circle.transparency,
plot.legend = FALSE,
legend.title = "",
plot.title = "",
legend.text.size = legend.text.size,
byRow = FALSE)})
names(plotList) <- IDs
return(plotList)
} else {
values.radar <- c("0.0", "0.5", "1.0")
grid.min <- 0
grid.mid <- 0.5
grid.max <- 1
centre.y <- grid.min - ((1/9)*(grid.max - grid.min))
plot.extent.x.sf <- 1
plot.extent.y.sf <- 1.2
x.centre.range <- 0.02*(grid.max - centre.y)
gridline.label.offset <- -0.1*(grid.max - centre.y)
gridline.min.linetype <- "longdash"
gridline.mid.linetype <- "longdash"
gridline.max.linetype <- "longdash"
plot.data <- as.data.frame(plot.data)
plot.data.min <- plot.data.max <- NULL
plot.data[,1] <- as.factor(as.character(plot.data[,1]))
names(plot.data)[1] <- "group"
var.names <- colnames(plot.data)[-1] #'Short version of variable names
#axis.labels [if supplied] is designed to hold 'long version' of variable
#names with line-breaks indicated using \n
#caclulate total plot extent as radius of outer circle x a user-specifiable
#scaling factor
plot.extent.x <- (grid.max + abs(centre.y))*plot.extent.x.sf
plot.extent.y <- (grid.max + abs(centre.y))*plot.extent.y.sf
#Check supplied data makes sense
if (length(axis.labels) != ncol(plot.data) - 1)
stop("'axis.labels' contains the wrong number of axis labels")
if (min(plot.data[,-1]) < centre.y)
stop("plot.data' contains value(s) < centre.y")
if (max(plot.data[,-1]) > grid.max)
stop("'plot.data' contains value(s) > grid.max")
#Declare required internal functions
CalculateGroupPath <- function(df) {
#Converts variable values into a set of radial x-y coordinates
#Code adapted from a solution posted by Tony M to
#http://stackoverflow.com/questions/9614433/creating-radar-chart-a-k-a-star-plot-spider-plot-using-ggplot2-in-r
#Args:
# df: Col 1 - group ('unique' cluster / group ID of entity)
# Col 2-n: v1.value to vn.value - values (e.g. group/cluser mean or
# median) of variables v1 to v.n
path <- as.factor(df[,1])
##find increment
angles <- seq(from = 0, to = 2*pi, by = (2*pi)/(ncol(df) - 1))
##create graph data frame
graphData <- data.frame(seg = "", x = 0, y = 0)
graphData <- graphData[-1,]
for (i in levels(path)) {
pathData <- subset(df, df[,1] == i)
for (j in c(2:ncol(df))) {
#pathData[,j]= pathData[,j]
graphData <- rbind(graphData,
data.frame(group = i,
x = pathData[,j]*sin(angles[j - 1]),
y = pathData[,j]*cos(angles[j - 1])))
}
##complete the path by repeating first pair of coords in the path
graphData <- rbind(graphData,
data.frame(group = i,
x = pathData[,2]*sin(angles[1]),
y = pathData[,2]*cos(angles[1])))
}
#Make sure that name of first column matches that of input data (in case
#!="group")
colnames(graphData)[1] <- colnames(df)[1]
graphData #data frame returned by function
}
CaclulateAxisPath <- function(var.names,min,max) {
#Caculates x-y coordinates for a set of radial axes (one per variable
#being plotted in radar plot)
#Args:
#var.names - list of variables to be plotted on radar plot
#min - MININUM value required for the plotted axes (same value will be
#applied to all axes)
#max - MAXIMUM value required for the plotted axes (same value will be
#applied to all axes)
#var.names <- c("v1","v2","v3","v4","v5")
n.vars <- length(var.names) # number of vars (axes) required
#Cacluate required number of angles (in radians)
angles <- seq(from = 0, to = 2*pi, by = (2*pi)/n.vars)
#calculate vectors of min and max x+y coords
min.x <- min*sin(angles)
min.y <- min*cos(angles)
max.x <- max*sin(angles)
max.y <- max*cos(angles)
#Combine into a set of uniquely numbered paths (one per variable)
axisData <- NULL
for (i in 1:n.vars) {
a <- c(i,min.x[i],min.y[i])
b <- c(i,max.x[i],max.y[i])
axisData <- rbind(axisData, a, b)
}
#Add column names + set row names = row no. to allow conversion into a
#data frame
colnames(axisData) <- c("axis.no","x","y")
rownames(axisData) <- seq(1:nrow(axisData))
#Return calculated axis paths
as.data.frame(axisData)
}
funcCircleCoords <- function(center = c(0,0), r = 1, npoints = 100){
#Adapted from Joran's response to
#http://stackoverflow.com/questions/6862742/draw-a-circle-with-ggplot2
tt <- seq(0,2*pi,length.out = npoints)
xx <- center[1] + r * cos(tt)
yy <- center[2] + r * sin(tt)
return(data.frame(x = xx, y = yy))
}
### Convert supplied data into plottable format
#(a) add abs(centre.y) to supplied plot data [creates plot centroid of 0,0
#for internal use, regardless of min. value of y in user-supplied data]
plot.data.offset <- plot.data
plot.data.offset[,2:ncol(plot.data.offset)] <-
plot.data[,2:ncol(plot.data)] + abs(centre.y)
#print(plot.data.offset)
# (b) convert into radial coords
group <- NULL
group$path <- CalculateGroupPath(plot.data.offset)
#print(group$path)
# (c) Calculate coordinates required to plot radial variable axes
axis <- NULL
axis$path <- CaclulateAxisPath(var.names,
grid.min + abs(centre.y),
grid.max + abs(centre.y))
#print(axis$path)
# (d) Create file containing axis labels + associated plotting coordinates
#Labels
axis$label <- data.frame(
text = axis.labels,
x = NA,
y = NA )
#print(axis$label)
#axis label coordinates
n.vars <- length(var.names)
angles <- seq(from = 0, to = 2*pi, by = (2*pi)/n.vars)
axis$label$x <- sapply(1:n.vars,
function(i, x) {
((grid.max + abs(centre.y))*axis.label.offset)*sin(angles[i])
})
axis$label$y <- sapply(1:n.vars,
function(i, x) {
((grid.max + abs(centre.y))*axis.label.offset)*cos(angles[i])
})
#print(axis$label)
# (e) Create Circular grid-lines + labels
#caclulate the coordinates required to plot circular grid-lines for three
#user-specified
#y-axis values: min, mid and max [grid.min; grid.mid; grid.max]
gridline <- NULL
gridline$min$path <- funcCircleCoords(c(0,0),
grid.min + abs(centre.y),
npoints = 360)
gridline$mid$path <- funcCircleCoords(c(0,0),
grid.mid + abs(centre.y),
npoints = 360)
gridline$max$path <- funcCircleCoords(c(0,0),
grid.max + abs(centre.y),
npoints = 360)
#print(head(gridline$max$path))
#gridline labels
gridline$min$label <- data.frame(x = gridline.label.offset,
y = grid.min + abs(centre.y),
text = as.character(grid.min))
gridline$max$label <- data.frame(x = gridline.label.offset,
y = grid.max + abs(centre.y),
text = as.character(grid.max))
gridline$mid$label <- data.frame(x = gridline.label.offset,
y = grid.mid + abs(centre.y),
text = as.character(grid.mid))
#print(gridline$min$label)
#print(gridline$max$label)
#print(gridline$mid$label)
### Start building up the radar plot
# Declare 'theme_clear', with or without a plot legend as required by user
#[default = no legend if only 1 group [path] being plotted]
theme_clear <- ggplot2::theme_bw(base_size = 20) +
ggplot2::theme(axis.text.y = ggplot2::element_blank(),
axis.text.x = ggplot2::element_blank(),
axis.ticks = ggplot2::element_blank(),
panel.grid.major = ggplot2::element_blank(),
panel.grid.minor = ggplot2::element_blank(),
panel.border = ggplot2::element_blank(),
legend.key = ggplot2::element_rect(linetype = "blank"))
#Base-layer = axis labels + plot extent
# [need to declare plot extent as well, since the axis labels don't always
# fit within the plot area automatically calculated by ggplot, even if all
# included in first plot; and in any case the strategy followed here is to
# first plot right-justified labels for axis labels to left of Y axis for x<
# (-x.centre.range)], then centred labels for axis labels almost immediately
# above/below x= 0 [abs(x) < x.centre.range]; then left-justified axis
# labels to right of Y axis [x>0]. This building up the plot in layers
# doesn't allow ggplot to correctly identify plot extent when plotting first
# (base) layer]
#base layer = axis labels for axes to left of central y-axis [x< -(x.centre.range)]
base <- ggplot2::ggplot(axis$label) +
ggplot2::xlab(NULL) +
ggplot2::ylab(NULL) +
ggplot2::coord_equal() +
ggplot2::geom_text(data = subset(axis$label,axis$label$x < (-x.centre.range)),
ggplot2::aes(x = x, y = y, label = text),
size = axis.label.size, hjust = 1) +
ggplot2::scale_x_continuous(limits = c(-1.5*plot.extent.x,
1.5*plot.extent.x)) +
ggplot2::scale_y_continuous(limits = c(-plot.extent.y,
plot.extent.y)) +
ggplot2::geom_text(data = subset(axis$label,
abs(axis$label$x) <= x.centre.range),
ggplot2::aes(x = x, y = y, label = text),
size = axis.label.size, hjust = 0.5) +
ggplot2::geom_text(data = subset(axis$label,
axis$label$x > x.centre.range),
ggplot2::aes(x = x, y = y, label = text),
size = axis.label.size, hjust = 0) +
ggplot2::labs(colour = legend.title,
size = legend.text.size) +
ggplot2::geom_polygon(data = gridline$max$path,
ggplot2::aes(x,y),
fill = background.circle.colour,
alpha = background.circle.transparency) +
ggplot2::geom_path(data = axis$path,
ggplot2::aes(x = x, y = y,
group = axis.no),
colour = axis.line.colour)
base <- base +
ggplot2::geom_path(data = group$path,
ggplot2::aes(x = x, y = y,
group = group, colour = group),
size = group.line.width) +
ggplot2::geom_point(data = group$path,
ggplot2::aes(x = x, y = y,
group = group, colour = group),
size = group.point.size) +
ggplot2::geom_path(data = gridline$min$path,
ggplot2::aes(x = x, y = y),
lty = gridline.min.linetype,
colour = gridline.min.colour,
size = grid.line.width) +
ggplot2::geom_path(data = gridline$mid$path,
ggplot2::aes(x = x, y = y),
lty = gridline.mid.linetype,
colour = gridline.mid.colour,
size = grid.line.width) +
ggplot2::geom_path(data = gridline$max$path,
ggplot2::aes(x = x, y = y),
lty = gridline.max.linetype,
colour = gridline.max.colour,
size = grid.line.width) +
ggplot2::geom_text(data = gridline$min$label,
ggplot2::aes(x = x, y = y,
label = values.radar[1]),
size = grid.label.size*0.8,
hjust = 1) +
ggplot2::geom_text(data = gridline$mid$label,
ggplot2::aes(x = x, y = y,
label = values.radar[2]),
size = grid.label.size*0.8,
hjust = 1) +
ggplot2::geom_text(data = gridline$max$label,
ggplot2::aes(x = x, y = y,
label = values.radar[3]),
size = grid.label.size*0.8,
hjust = 1) +
theme_clear +
ggplot2::theme(legend.key.width = ggplot2::unit(3,"line")) +
ggplot2::theme(text = ggplot2::element_text(size = 20)) +
ggplot2::theme(legend.text = ggplot2::element_text(size = legend.text.size),
legend.position = "left") +
ggplot2::theme(legend.key.height = ggplot2::unit(2,"line")) +
ggplot2::scale_colour_manual(values =
rep(c("#FF5A5F", "#FFB400",
"#007A87", "#8CE071",
"#7B0051", "#00D1C1",
"#FFAA91", "#B4A76C",
"#9CA299", "#565A5C",
"#00A04B", "#E54C20"),
100))
if (!plot.legend) {
base <- base +
ggplot2::theme(legend.position = "none")
}
if (plot.title != "") {
base <- base +
ggplot2::ggtitle(plot.title)
}
return(base)
}
}
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