plot.DiffusionMap: 3D or 2D plot of diffusion map
In theislab/destiny: Creates diffusion maps

plot.DiffusionMap

R Documentation

3D or 2D plot of diffusion map

Description

If you want to plot the eigenvalues, simply plot(eigenvalues(dm)[start:end], ...)

Usage

plot.DiffusionMap(
  x,
  dims = 1:3,
  new_dcs = if (!is.null(new_data)) dm_predict(x, new_data),
  new_data = NULL,
  col = NULL,
  col_by = NULL,
  col_limits = NULL,
  col_new = "red",
  pal = NULL,
  pal_new = NULL,
  ...,
  ticks = FALSE,
  axes = TRUE,
  box = FALSE,
  legend_main = col_by,
  legend_opts = list(),
  interactive = FALSE,
  draw_legend = !is.null(col_by) || (length(col) > 1 && !is.character(col)),
  consec_col = TRUE,
  col_na = "grey",
  plot_more = function(p, ..., rescale = NULL) p
)

## S4 method for signature 'DiffusionMap,numeric'
plot(x, y, ...)

## S4 method for signature 'DiffusionMap,missing'
plot(x, y, ...)

Arguments

`x`	A DiffusionMap
`dims`, `y`	Diffusion components (eigenvectors) to plot (default: first three components; 1:3)
`new_dcs`	An optional matrix also containing the rows specified with `y` and plotted. (default: no more points)
`new_data`	A data set in the same format as `x` that is used to create `new_dcs <- dm_predict(dif, new_data)`
`col`	Single color string or vector of discrete or categoric values to be mapped to colors. E.g. a column of the data matrix used for creation of the diffusion map. (default: `cluster_louvain` if igraph is installed)
`col_by`	Specify a `dataset(x)` or `phenoData(dataset(x))` column to use as color
`col_limits`	If `col` is a continuous (=double) vector, this can be overridden to map the color range differently than from min to max (e.g. specify `c(0, 1)`)
`col_new`	If `new_dcs` is given, it will take on this color. A vector is also possible. (default: red)
`pal`	Palette used to map the `col` vector to colors. (default: use `hcl.colors` for continuous and `palette()` for discrete data)
`pal_new`	Palette used to map the `col_new` vector to colors. (default: see `pal` argument)
`...`	Parameters passed to plot, scatterplot3d, or plot3d (if `interactive == TRUE`)
`ticks`	logical. If TRUE, show axis ticks (default: FALSE)
`axes`	logical. If TRUE, draw plot axes (default: Only if `ticks` is TRUE)
`box`	logical. If TRUE, draw plot frame (default: TRUE or the same as `axes` if specified)
`legend_main`	Title of legend. (default: nothing unless `col_by` is given)
`legend_opts`	Other colorlegend options (default: empty list)
`interactive`	Use plot3d to plot instead of scatterplot3d?
`draw_legend`	logical. If TRUE, draw color legend (default: TRUE if `col_by` is given or `col` is given and a vector to be mapped)
`consec_col`	If `col` or `col_by` refers to an integer column, with gaps (e.g. `c(5,0,0,3)`) use the palette color consecutively (e.g. `c(3,1,1,2)`)
`col_na`	Color for `NA` in the data. specify `NA` to hide.
`plot_more`	Function that will be called while the plot margins are temporarily changed (its `p` argument is the rgl or scatterplot3d instance or NULL, its `rescale` argument is `NULL`, a `list(from = c(a, b), to = c(c, d))`), or an array of shape `from\|to \times dims \times min\|max`, i.e. `2 \times length(dims) \times 2`. In case of 2d plotting, it should take and return a ggplot2 object.