plot_fcomp: Plot mean performances of assemblages containing a given...
In functClust: Functional Clustering of Redundant Components of a System

Description Usage Arguments Details Value See Also

The function plots, as vertical or horizontal boxplots, the mean performances of assemblages containing a given component.

1	plot_fcomp(fres, nbcl = 0, main = "Title", opt.comp = NULL )

`fres`	an object generated by the function `fclust`.
`nbcl`	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.
`main`	a string, that is used as the first, reference part of the title of each graph.
`opt.comp`	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)`.

None.

Nothing. It is a procedure.

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