plot_hex {DecomposeR}

Group and/or log-scale hexagonal binning

Description

Group and/or log-scale hexagonal binning. Provides a legend indicating the count representations. USES THE GRID GRAPHICAL SYSTEM, BASE GRAPHICS NOT SUPPORTED. To add lines, polygons or text, use the l, g and t arguments.

Usage

plot_hex(
  x,
  y,
  id = NA,
  select = NA,
  uniform = TRUE,
  bins = 60,
  xbnds = range(x, na.rm = TRUE),
  ybnds = range(y, na.rm = TRUE),
  xlim = xbnds,
  ylim = ybnds,
  log = "",
  shape = 1,
  mincnt = 1,
  maxcnt = NA,
  colorcut = seq(0, 1, length = 17),
  colramp = function(n) matlab.like(length(colorcut) - 1),
  trans = NULL,
  inv = NULL,
  border = NULL,
  lwd = 0.1,
  cex = 1,
  main = "",
  xlab = "x",
  ylab = "y",
  xaxis = TRUE,
  yaxis = TRUE,
  xaxs = "r",
  yaxs = "r",
  box = TRUE,
  mar = c(0.15, 0.125, 0.15, 0.2),
  legend = TRUE,
  leg_sep = 0.1,
  xpd_hex = 0.75,
  xpd_leg = 1.5,
  l = list(x = NULL, y = NULL, default.units = "native"),
  g = list(x = NULL, y = NULL, default.units = "native"),
  t = list(label = NULL, default.units = "native"),
  plot = TRUE
)

Arguments

x, y

vectors giving the coordinates of the bivariate data points to be binned.

id

a vector of ids for each x value, to separate different groups of data

select

the groups of ids to plot

uniform

whether to keep the creaks defined by the entire matrixes when selecting only a part of it

bins

the number of bins partitioning the range of xbnds.

xbnds, ybnds

horizontal and vertical limits of the binning region in x or y units respectively; must be numeric vector of length 2.

xlim, ylim

the limits of the plot

log

a character string which contains "x" if the x axis is to be logarithmic, "y" if the y axis is to be logarithmic and "xy" or "yx" if both axes are to be logarithmic.

shape

the theoretical shape = yheight/xwidth of the plotting. This adapts the form of the hexagons accordingly.

mincnt, maxcnt

fraction of cell area for the lowest and largest count, respectively

colorcut

vector of values covering [0, 1] that determine hexagon color class boundaries and hexagon legend size boundaries. Alternatively, an integer (<= maxcnt) specifying the number of equispaced colorcut values in [0,1].

colramp

function accepting an integer n as an argument and returning n colors.

trans

a transformation function for the counts such as log10

inv

the inverse transformation function (if trans = log10, inv should for instance be function(x) 10^x.

border

the color of the border of the hexagons. By default it will be the color of the filling

lwd

the width of the border of the hexagons.

cex

the magnification of text.

main

main title.

xlab, ylab

x and y axis labels respectively.

xaxis, yaxis

whether to plot the x and y axes respectively.

xaxs, yaxs

The style of axis interval calculation to be used for the axes. By default the style "r" (regular) first extends the data range by 4 percent at each end and then finds an axis with pretty labels that fits within the extended range. Style "i" (internal) just finds an axis with pretty labels that fits within the original data range.

box

whether to plot a box.

mar

a numerical vector of the form c(bottom, left, top, right) which gives the room the give to the margins in Normalised Parent Coordinates (see grid package for more information)

legend

whether to plot the legend.

leg_sep

the distance between hexagons and text f the legend in Normalised Parent Coordinates left on the right margin

xpd_hex

factor to expand the legend hexagons

xpd_leg

factor to expand the height of the legend

l

a list of arguments to feed to grid::grid.polyline ATTENTION the grid package has to be loaded

g

a list of arguments to feed to grid::grid.polygon ATTENTION the grid package has to be loaded

t

a list of arguments to feed to grid::grid.text ATTENTION the grid package has to be loaded

plot

whether to plot. If FALSE, returns a grob.

Examples

library(grid) # To use the gpar function

set.seed(42)

n <- 600
t <- seq_len(n)

p1 <- 30
p2 <- 240

xy <- (1 + 0.6 * sin(t*2*pi/p2)) * sin(t*2*pi/p1)  + 2 * sin(t*2*pi/p2) +
        rnorm(n, sd = 0.5)

inter_dt <- round(runif(length(xy), min = 0.5, max = 1.5),1)

dt <- cumsum(inter_dt)

dec <- extricate(xy, dt, nimf = 7, sifting = 10,
                repl = 10, comb = 10, factor_noise = 10,
                 speak = FALSE)

## Not run: 
plot_emd(dec, dir = tempdir())
## End(Not run)

integrity(xy, dec)
parsimony(dec)

ht  <- inst.pulse(dec, plot = FALSE)

plot_hex(x = 1/ht$f, y = ht$a, bins = 100, ybnds = c(0,2),
         log = "x", trans = log10, inv = function(x) 10^x,
         main = "Spectral Population", xlab = "Period", ylab = "Amplitude")

plot_hex(x = 1/ht$f, y = ht$a, bins = 100, ybnds = c(0,2),
         log = "x", trans = log10, inv = function(x) 10^x,
         main = "Spectral Population", xlab = "Period", ylab = "Amplitude",
         id = ht$mode, select = c(4,6,7),
         l = list(x = c(30, 30, 240, 240), y = unit(c(0,1,0,1), "npc"),
                 id = c(1,1,2,2), gp = gpar(col = c("red", "blue"), lwd = 2)),
        g = list(x = c(18, 50, 50, 18, 18, 50, 50, 18),
                 y = c(0, 0, 1.9, 1.9, 2.05, 2.05, 1.95, 1.95),
                 id = c(1,1,1,1,2,2,2,2),
                 gp = gpar(col = c("red", NA), fill = c(NA, "white"), lwd = 2)),
        t = list(label = "Mode 4", x = 30, y = 2, gp = gpar(col = "red")))