plotcomp: Plot extracted components
In nicolaroberts/hdp: Hierarchical Dirichlet Process for categorical count data

Plot extracted components

plot_comp_size(hdpsample, legend = TRUE, col_a = "hotpink",
  col_b = "skyblue3", xlab = "Component", ylab = "Number of data items",
  ...)

plot_comp_distn(hdpsample, comp = NULL, cat_names = NULL, grouping = NULL,
  col = "grey70", col_nonsig = NULL, show_group_labels = FALSE,
  cred_int = TRUE, weights = NULL, plot_title = NULL,
  group_label_height = 1.05, cex.cat = 0.7, ...)

plot_dp_comp_exposure(hdpsample, dpindices, col_comp, dpnames = NULL,
  main_text = NULL, incl_numdata_plot = TRUE, incl_nonsig = TRUE,
  incl_comp0 = TRUE, ylab_numdata = "Number of data items",
  ylab_exp = "Component exposure", leg.title = "Component",
  cex.names = 0.6, cex.axis = 0.7, mar = c(1, 4, 2, 0.5), oma = c(1.5,
  1.5, 1, 1), ...)

`hdpsample`	A hdpSampleChain or hdpSampleMulti object including output from `hdp_extract_components`
`legend`	Logical - should a legend be included? (default TRUE)
`col_a`	Color ramp side for early posterior samples (if hdpSampleChain) or first chain (if hdpSampleMulti)
`col_b`	Color ramp side for late posterior samples (if hdpSampleChain) or last chain (if hdpSampleMulti)
`xlab`	Horizontal axis label
`ylab`	Vertical axis label
`...`	Other arguments to plot
`comp`	(Optional) Number(s) of the component(s) to plot (from 0 to the max component number). The default is to plot all components.
`cat_names`	(Optional) Data category names to label the horizontal axis
`grouping`	(Optional) A factor indicating data category groups.
`col`	Either a single colour for all data categories, or a vector of colours for each group (in the same order as the levels of the grouping factor)
`col_nonsig`	(Optional) Colour for any data category whose 95% credibility interval overlaps with zero (if set, overrides col argument)
`show_group_labels`	Logical - should group labels be added to the top horizontal axis? (default FALSE) (only works if categories alreayd come in orders)
`cred_int`	Logical - should 95% credibility intervals be plotted? (default TRUE)
`weights`	(Optional) Weights over the data categories to adjust their relative contribution (multiplicative)
`plot_title`	(Optional) Character vector of custom plot titles (one for each component plotted)
`group_label_height`	Multiplicative factor from top of plot for group label placement
`cex.cat`	Expansion factor for the (optional) cat_names
`dpindices`	Indices of DP nodes to plot
`col_comp`	Colours of each component, from 0 to the max number
`dpnames`	(Optional) Names of the DP nodes
`main_text`	(Optional) Text at top of plot
`incl_numdata_plot`	Logical - should an upper barplot indicating the number of data items per DP be included? (Default TRUE)
`incl_nonsig`	Logical - should components whose credibility intervals include 0 be included (per DP)? (Default TRUE)
`incl_comp0`	Logical - should component zero be plotted? (Default TRUE)
`ylab_numdata`	Vertical axis label for numdata plot
`ylab_exp`	Vertical exis label for exposure plot
`leg.title`	Legend title
`cex.names`	Expansion factor for bar labels (dpnames) in exposure plot
`cex.axis`	Expansion factor for vertical-axis annotation
`mar`	See ?par
`oma`	See ?par

mut_example_multi <- hdp_extract_components(mut_example_multi)
plot_comp_size(mut_example_multi, bty="L")
bases <- c("A", "C", "G", "T")
trinuc_context <- paste0(rep(rep(bases, times=6), each=4),
                         rep(c("C", "T"), each=48),
                         rep(bases, times=24))
group_factor <- as.factor(rep(c("C>A", "C>G", "C>T", "T>A", "T>C", "T>G"),
                           each=16))
plot_comp_distn(mut_example_multi, cat_names=trinuc_context,
                grouping=group_factor, col=RColorBrewer::brewer.pal(6, "Set2"),
                col_nonsig="grey80", show_group_labels=TRUE)
plot_dp_comp_exposure(mut_example_multi, 5:30,
                      RColorBrewer::brewer.pal(12, "Set3"))
plot_dp_comp_exposure(mut_example_multi, 5:30,
                      RColorBrewer::brewer.pal(12, "Set3"),
                      incl_numdata_plot=FALSE, incl_nonsig=FALSE)