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plot.mlist
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## (3) plot.mlist() ##
# DESCRIPTION: Use base::plot to visualize number of pairs in each bin for "mlist".
# REQUIRES: an "mlist" from binneR() and the source distance matrix (XY).
# ARGUMENTS:
#
# leg : logical indicating whether or not to plot a legend (default = TRUE)
# lseg : logical indicating whether or not to draw vertical ablines only (default = TRUE)
# pcounts : logical indicating whether to plot pair counts in top margin of each bin (default = FALSE)
# START
plot.mlist <- function(mlist, XY, leg = TRUE, lseg = TRUE, pcounts = FALSE){
lower_vect <- XY[lower.tri(XY)]
sort_vect <- sort(lower_vect)
bins <- length(mlist$bin_list)
if (mlist$type == "ep"){
plot(sort_vect ~ c(1:length(sort_vect)),
xlab = list("Pair Count", cex = 1.2),
ylab = list("Pairwise distance", cex = 1.2),
main = paste("~ Equal number of pairs in each bin (n = ",bins,")", sep = ""))
quantile_dists <- mlist$boundaries
v_lines <- match(quantile_dists, sort_vect)
if (lseg == TRUE){
segments(v_lines[1], 0,
v_lines[1], quantile_dists[1],
lty = 3,
col = "orange")
segments(v_lines[2:length(v_lines)], c(rep(0, length(v_lines) - 1)),
v_lines[2:length(v_lines)], quantile_dists[2:length(quantile_dists)],
lty = 3,
col = "red3")
segments(c(rep(0,length(quantile_dists) - 1)), quantile_dists[2:length(quantile_dists)],
v_lines[2:length(v_lines)], quantile_dists[2:length(quantile_dists)],
lty = 2,
col = "gray50")
} else if (lseg == FALSE){
abline(v = v_lines, col = "red3", lty = 3)
abline(v = v_lines [1], col = "orange", lty = 3)
abline(h = quantile_dists, col = "gray50", lty = 2)
abline(h = quantile_dists[1], col = "yellow", lty = 2)
}
# obtain counts in each class for plotting
limits <- cut(sort_vect, quantile_dists)
counts <- unname(table(limits))
# add labels to counts for legend box
leg_labels <- numeric(bins)
for (i in 1:bins){
leg_labels[i] <- paste("n", i, sep = "")
}
leg_items <- numeric(bins)
for (j in 1:bins){
leg_items[j] <- paste(leg_labels[j], ":" , counts[j], sep = "")
}
if (pcounts == TRUE){
scale_cex <- (1 / bins) * 4.5
mtext(counts, at = cumsum(counts) - counts / 2, side = 3, cex = scale_cex)
}
if (leg == TRUE){
legend("bottomright", legend = leg_items, bg = "white", cex = 0.8)
}
} else if (mlist$type == "cd"){
if (pcounts == TRUE){
stop("pcounts=TRUE is only available for type='ep'; use the default setting")
}
# remove all pairwise distances above the upper class boundary
upper_boundaries <- mlist$boundaries[-1]
max_limit <- max(upper_boundaries)
cut_vect <- sort_vect[sort_vect <= max_limit]
plot(cut_vect ~ c(1:length(cut_vect)),
xlab = list("Pair Count", cex = 1.2),
ylab = list("Pairwise distance", cex = 1.2),
main = paste("Custom distance classes (n = ", length(upper_boundaries), ")", sep = ""))
# Identify the vector index for upper boundary of each class
positions <- numeric(length(upper_boundaries))
for (i in 1:length(positions)){
positions[i] <- max(which(cut_vect <= upper_boundaries[i]))
}
# cut sort vect into groups of distancies based on mlist$boundaries
bins <- cut(sort_vect, mlist$boundaries)
counts <- unname(table(bins)) #get counts in classes
# add position 0 to positions so that lines originate at origin
positions <- c(0, positions)
if (lseg == TRUE){
segments(0, 0,
0, mlist$boundaries[1],
lty = 3,
col = "orange")
segments(positions[2:length(positions)], c(rep(0,length(positions)-1)),
positions[2:length(positions)], mlist$boundaries[2:length(mlist$boundaries)],
lty = 3,
col = "red3")
segments(c(rep(0,length(positions) - 1)), mlist$boundaries[2:length(mlist$boundaries)],
positions[2:length(positions)], mlist$boundaries[2:length(mlist$boundaries)],
lty = 2,
col = "gray50")
} else if (lseg == FALSE){
abline(v = positions, col = "red3", lty = 3)
abline(v = positions[1], col = "orange", lty = 3)
abline(h = upper_boundaries, col = "gray50", lty = 2)
abline(h = min(cut_vect), col = "yellow", lty = 2)
}
# add labels to counts for legend box
leg_labels <- numeric(length(upper_boundaries))
for (j in 1:length(upper_boundaries)){
leg_labels[j] <- paste("n", j, sep = "")
}
leg_items <- numeric(length(upper_boundaries))
for (k in 1:length(upper_boundaries)){
leg_items[k] <- paste(leg_labels[k], ":", counts[k], sep = "")
}
if (leg == TRUE){
legend("bottomright", legend = leg_items, bg = "white", cex = 0.8)
}
} else if (mlist$type == "pc"){
if (pcounts == TRUE){
stop("pcounts=TRUE is only available for type='ep'; use the default setting")
}
#identify positions on x axis via cumulative sum of number of pairs in each bin; then add first position
pair_count <- cumsum(mlist$bin_count)
pair_count.1 <- c(1, pair_count)
#trim the vector of pairwise distances
cut_vect <- sort_vect[1:max(pair_count)]
plot(cut_vect ~ c(1:max(pair_count)),
xlab = list("Pair Count", cex = 1.2),
ylab = list("Pairwise distance", cex = 1.2),
main = paste(mlist$bin_count[1], " pairs per bin; ", length(mlist$bin_list)," bins"))
if (lseg == TRUE){
segments(0, 0,
0, mlist$boundaries[1],
lty = 3,
col = "orange")
segments(pair_count.1[2:length(pair_count.1)], c(rep(0, length(mlist$boundaries) - 1)),
pair_count.1[2:length(pair_count.1)], mlist$boundaries[2:length(mlist$boundaries)],
lty = 3,
col = "red3")
segments(c(rep(0,length(pair_count.1) - 1)), mlist$boundaries[2:length(mlist$boundaries)],
pair_count.1[2:length(pair_count.1)], mlist$boundaries[2:length(mlist$boundaries)],
lty = 2,
col = "gray50")
} else if (lseg == FALSE){
abline(v = pair_count.1, col = "red3", lty = 3)
abline(v = pair_count.1[1], col = "orange", lty = 3)
abline(h = mlist$boundaries, col = "gray50", lty = 2)
abline(h = mlist$boundaries[1], col = "yellow", lty = 2)
}
#add labels to counts for legend box
leg_labels <- numeric(length(mlist$bin_count))
for (j in 1:length(mlist$bin_count)){
leg_labels[j] <- paste("d", j, sep = "")
}
leg_items <- numeric(length(mlist$bin_count))
distances <- round(mlist$boundaries[-1], 1)
for (k in 1:length(mlist$bin_count)){
leg_items[k] <- paste(leg_labels[k], ":", distances[k], sep = "")
}
if (leg == TRUE){
legend("bottomright", legend = leg_items, bg = "white", cex = 0.8)
}
}
}
# END