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#' @name plotHVT
#' @title Plot the hierarchical tesselations.
#'
#' Main plotting function to construct hierarchical voronoi tessellations.
#'
#' @param hvt.results List. A list containing the ouput of \code{HVT} function
#' which has the details of the tessellations to be plotted.
#' @param line.width Numeric Vector. A vector indicating the line widths of the
#' tessellation boundaries for each level.
#' @param color.vec Vector. A vector indicating the colors of the boundaries of
#' the tessellations at each level.
#' @param pch1 Numeric. Symbol type of the centroids of the tessellations
#' (parent levels). Refer \code{\link{points}}. (default = 21)
#' @param centroid.size Numeric. Size of centroids of first level
#' tessellations. (default = 3)
#' @param title String. Set a title for the plot. (default = NULL)
#' @param maxDepth Numeric. An integer indicating the number of levels. (default = NULL)
#' @author Shubhra Prakash <shubhra.prakash@@mu-sigma.com>, Sangeet Moy Das <sangeet.das@@mu-sigma.com>
#' @seealso \code{\link{HVT}} \cr \code{\link{hvtHmap}}
#' @keywords hplot
#' @importFrom magrittr %>%
#' @import ggplot2
#' @examples
#'
#' data("USArrests",package="datasets")
#'
#' hvt.results <- list()
#' hvt.results <- HVT(USArrests, n_cells = 15, depth = 1, quant.err = 0.2,
#' distance_metric = "L1_Norm", error_metric = "mean",
#' projection.scale = 10, normalize = TRUE,
#' quant_method="kmeans",diagnose=TRUE)
#' plotHVT(hvt.results, line.width = c(0.8), color.vec = c('#141B41'),
#' maxDepth = 1)
#'
#' @export plotHVT
library(ggplot2)
plotHVT <-
function(hvt.results,
line.width,
color.vec,
pch1 = 21,
centroid.size = 1.5,
title = NULL,
maxDepth=NULL) {
# browser()
hvt_list <- hvt.results
maxDepth = min(maxDepth,max(hvt_list[[3]][["summary"]] %>% stats::na.omit() %>% dplyr::select("Segment.Level")))
min_x = 1e9
min_y = 1e9
max_x = -1e9
max_y = -1e9
depthVal = c()
clusterVal = c()
childVal = c()
value = c()
x_pos = c()
y_pos = c()
x_cor = c()
y_cor = c()
depthPos = c()
clusterPos = c()
childPos = c()
levelCluster = c()
for (clusterNo in 1:length(hvt_list[[2]][[1]][[1]])) {
bp_x = hvt_list[[2]][[1]][[1]][[clusterNo]][["x"]]
bp_y = hvt_list[[2]][[1]][[1]][[clusterNo]][["y"]]
if (min(bp_x) < min_x)
min_x = min(bp_x)
if (max(bp_x) > max_x)
max_x = max(bp_x)
if (min(bp_y) < min_y)
min_y = min(bp_y)
if (max(bp_y) > max_y)
max_y = max(bp_y)
}
for (depth in 1:maxDepth) {
for (clusterNo in 1:length(hvt_list[[2]][[depth]])) {
for (childNo in 1:length(hvt_list[[2]][[depth]][[clusterNo]])) {
current_cluster = hvt_list[[2]][[depth]][[clusterNo]][[childNo]]
x = as.numeric(current_cluster[["x"]])
y = as.numeric(current_cluster[["y"]])
x_cor = c(x_cor, as.numeric(current_cluster[["pt"]][["x"]]))
y_cor = c(y_cor, as.numeric(current_cluster[["pt"]][["y"]]))
depthVal = c(depthVal, depth)
clusterVal = c(clusterVal, clusterNo)
childVal = c(childVal, childNo)
depthPos = c(depthPos, rep(depth, length(x)))
clusterPos = c(clusterPos, rep(clusterNo, length(x)))
childPos = c(childPos, rep(childNo, length(x)))
x_pos = c(x_pos, x)
y_pos = c(y_pos, y)
levelCluster = c(levelCluster, depth)
}
}
}
valuesDataframe <- data.frame(depth = depthVal,
cluster = clusterVal,
child = childVal)
positionsDataframe <- data.frame(
depth = depthPos,
cluster = clusterPos,
child = childPos,
x = x_pos,
y = y_pos
)
centroidDataframe <-
data.frame(x = x_cor, y = y_cor, lev = levelCluster)
datapoly <-
merge(valuesDataframe,
positionsDataframe,
by = c("depth", "cluster", "child"))
p <- ggplot2::ggplot()
for (i in maxDepth:1) {
p <-
p + ggplot2::geom_polygon(
data = datapoly[which(datapoly$depth == i), ],
ggplot2::aes(
x = x,
y = y,
color = factor(depth),
size = factor(depth),
group = interaction(depth, cluster, child),
),
fill = NA
) +
ggplot2::scale_colour_manual(values = color.vec) +
ggplot2::scale_size_manual(values = line.width, guide = "none") +
ggplot2::labs(color = "Level")
}
for (depth in 1:maxDepth) {
p <- p + ggplot2::geom_point(
data = centroidDataframe[centroidDataframe["lev"] == depth, ],
ggplot2::aes(x = x, y = y),
size = (centroid.size / (2 ^ (depth - 1))),
pch = 21,
fill = color.vec[depth],
color = color.vec[depth] ) +
ggplot2::geom_point(
data = centroidDataframe[centroidDataframe["lev"] == depth, ],
ggplot2::aes(x = x, y = y),
size = (centroid.size / (2 ^ (depth - 1))),
pch = 21,
fill = color.vec[depth],
color = color.vec[depth] )
}
p <- p +
ggplot2::scale_color_manual(name = "Level",
values = color.vec) +
ggplot2::theme_bw() + ggplot2::theme(
plot.background = ggplot2::element_blank()
,
plot.title = element_text(
size = 20,
hjust = 0.5,
margin = margin(0, 0, 20, 0)
)
,
panel.grid = ggplot2::element_blank()
,
panel.border = ggplot2::element_blank()
,
axis.ticks = element_blank()
,
axis.text = element_blank()
,
axis.title = element_blank()
,
panel.background = element_blank()
) + ggplot2::theme(plot.title = element_text(hjust = 0.5)) +
ggplot2::scale_x_continuous(expand = c(0, 0)) +
ggplot2::scale_y_continuous(expand = c(0, 0)) +
ggplot2::geom_label(label = centroidDataframe$outlier_cell,
nudge_x=0.45, nudge_y=0.1,
check_overlap=T,
label.padding=unit(0.55, "lines"),
label.size=0.4,
color="white",
fill="#038225" )
return(suppressMessages(p))
}
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