Time Series Plot

Source: R/tsplot.R

Plot the time series row-wise.

tsplot(x, time.given = FALSE, num = nrow(x), sample.points = c(),
  mode = "lines", dist = "bray", my.color.map = list(),
  identifyPoints = FALSE, topN = 10, groups = c(),
  hideGroups = c(), legend = FALSE, labels = c(), noLabels = FALSE,
  centroid = FALSE, perturb = NULL, ...)

Arguments

x

the matrix of time series
time.given

if true, then the column names are supposed to hold the time units
num

the number of rows to plot (starting from the first row)
sample.points

indicate sample points (only for lines)
mode

lines (default), pcoa (a PCoA plot with arrows showing the community trajectory) or bars (a stacked barplot for each sample)
dist

the distance to use for the PCoA plot
my.color.map

map of taxon-specific colors, should match row names (only for bars) or group names (only for lines)
identifyPoints

click at points in the PCoA plot to identify them (using function identify), not active when noLabels is TRUE
topN

number of top taxa to be plotted for mode bars
groups

group membership vector; for mode bars and pcoa refers to samples; for mode lines refers to taxa; there are as many entries in the group membership vector as samples or taxa; taxa/samples are assumed to be ordered by groups
hideGroups

compute PCoA with all data, but do not show members of selected groups; expects one integer/name per group and consistency with groups parameter, only supported for mode pcoa
legend

add a legend
labels

use the provided labels in the PCoA plot
noLabels

do not use any labels in the PCoA plot
centroid

draw PCoA plot with a centroid (groups are ignored)
perturb

a perturbation object (adds polygons in mode lines highlighting the perturbation periods, colors labels in mode bars and colors dots in the PCoA plot)
\dots

Additional arguments passed to plot()

Examples

N=50
A=modifyA(generateA(N, c=0.1, d=-1),perc=70,strength="uniform",mode="negpercent")
#> [1] "Adjusting connectance to 0.1"
#> [1] "Initial edge number 2500"
#> [1] "Initial connectance 1"
#> [1] "Number of edges removed 2205"
#> [1] "Final connectance 0.1"
#> [1] "Final connectance: 0.1"
#> [1] "Initial edge number 295"
#> [1] "Initial connectance 0.1"
#> [1] "Number of negative edges already present: 177"
#> [1] "Converting 30 edges into negative edges"
#> [1] "Final connectance: 0.1"
out.ricker=ricker(N,A=A,y=generateAbundances(N,mode=5,prob=TRUE),K=rep(0.1,N), sigma=-1,tend=500)
tsplot(out.ricker, main="Ricker")
tsplot(out.ricker[,1:20],mode="bars",legend=TRUE)
tsplot(out.ricker[,1:50],mode="pcoa")
#> [1] "First five eigen values:"
#> [1] "1.84665547893296, 0.299730916240714, 0.0493988844847274, 0.0116453491873411, 0.00501010454139853"