The function plots, as vertical or horizontal boxplots, the mean performances of assemblages containing a given component.
plot_fcomp(fres, nbcl = 0, main = "Title", opt.comp = NULL )an object generated by the function fclust.
an integer.
The integer indicates the number of component clusters
to take into account.
It can be lower than or equals to
the optimum number fres$nbOpt of component clusters.
a string, that is used as the first, reference part of the title of each graph.
a list, that can include
opt.comp = list("tree", "perf", "hor", "ver", cols,
pvalue, "zoom", window, "all").
This option list manages the plot as boxplot
of observed mean performances
of assemblages that contain a given component,
horizontally or vertically,
components sorted by increasing or decreasing mean values,
or components sorted like the clustering tree.
The item order in list is any.
"tree", "perf": plot the observed mean performances
of assemblages that contain a given component as boxplots.
Each set of assemblages that contains a given component
is named by the contained component.
The coloured squares are the mean performances of assemblage sets.
Size (number of observed assemblages) of assemblage sets
is indicated on the left of boxplots.
The red dashed line is the mean performance of assemblage sets.
If "aov" is checked, groups significantly different
(at a p-value < pvalue) are indicated by differents letters
on the right of boxplots.
If "tree": is checked, mean performances
of assemblages that contain a given component
are sorted like the clustering tree.
If "perf" is checked, mean performances
of assemblages that contain a given component
are sorted by increasing mean performances.
"hor": plot boxplots as horizontal boxes:
x-axis corresponds to assemblage performances,
and y-axis corresponds to assemblage sets.
It "hor" is not checked,
boxplots are plotted as vertical boxes:
x-axis corresponds to assemblage sets,
and y-axis corresponds to assemblage performances.
Option "ver" can also be used: "ver" = !"hor".
cols: is a vector of integers, of same length
as the number of components. This option specifies
the colour of each component.
The components labelled by the same integer
have the same colour. If cols is not specified,
the components that belong to a same cluster
a posteriori determined have the same colour.
This option is useful when an a priori clustering is known,
to identify the components a priori clustered
into the a posteriori clustering.
pvalue = value: a probability used as threshold
in the variance analysis. Then pvalue must be
higher than 0 and lower than 1.
pvalue must be informed when "aov" is checked.
Groups significantly different
(at a p-value < pvalue) are then indicated by differents letters
on the right of boxplots.
"all": plot all possible graphs.
This option is equivalent to
opt.motif = list("tree", "aov", pvalue = 0.001,
"zoom", window = 20).
Nothing. It is a procedure.
None.
plot_ftrees plot primary and secondary trees
resulting from functional clustering
plot_fperf plot observed, modelled and predicted performances
resulting from functional clustering
plot_fass plot performances of some given assemblages
plot_fmotif plot as boxplot mean performances
of assemblages sorted by assembly motifs
plot_fcomp plot as boxplot mean performances
of assemblages containing a given component
fclust_plot plot all possible outputs
of functional clustering