tour_pairs: Tour Pairs Plot
In loon.tourr: Tour in 'Loon'

Description Usage Arguments Value See Also Examples

A nD tour path with a scatterplot matrix (the default tour is a 4D tour; by setting 'tour_path' to modify the dimension)

l_tour_pairs(
  data,
  scaling = c("data", "variable", "observation", "sphere"),
  tour_path = tourr::grand_tour(4L),
  numOfTours = 30L,
  interpolation = 40L,
  as.l_tour = TRUE,
  connectedScales = c("none", "cross"),
  linkingGroup,
  linkingKey,
  showItemLabels = TRUE,
  itemLabel,
  showHistograms = FALSE,
  histLocation = c("edge", "diag"),
  histHeightProp = 1,
  histArgs = list(),
  showSerialAxes = FALSE,
  serialAxesArgs = list(),
  color = "grey60",
  group = "color",
  start = NULL,
  parent = NULL,
  span = 10L,
  envir = parent.frame(),
  ...
)

`data`	a data frame with numerical data only
`scaling`	one of 'variable', 'data', 'observation', 'sphere', or 'none' to specify how the data is scaled. See Details
`tour_path`	tour path generator, defaults to 2d grand tour
`numOfTours`	the number of tours
`interpolation`	the steps between two serial projections. The larger the value is, the smoother the transitions would be.
`as.l_tour`	return a `l_tour` object; see details
`connectedScales`	Determines how the scales of the panels are to be connected. `"cross"`: only the scales in the same row and the same column are connected; `"none"`: neither "x" nor "y" scales are connected in any panels.
`linkingGroup`	string giving the linkingGroup for all plots. If missing, a default `linkingGroup` will be determined from deparsing the `data`.
`linkingKey`	a vector of strings to provide a linking identity for each row of the `data` data.frame. If missing, a default `linkingKey` will be `0:(nrows(data)-1)`.
`showItemLabels`	TRUE, logical indicating whether its itemLabel pops up over a point when the mouse hovers over it.
`itemLabel`	a vector of strings to be used as pop up information when the mouse hovers over a point. If missing, the default `itemLabel` will be the `row.names(data)`.
`showHistograms`	logical (default FALSE) to show histograms of each variable or not
`histLocation`	one "edge" or "diag", when showHistograms = TRUE
`histHeightProp`	a positive number giving the height of the histograms as a proportion of the height of the scatterplots
`histArgs`	additional arguments to modify the 'l_hist' states
`showSerialAxes`	logical (default FALSE) indication of whether to show a serial axes plot in the bottom left of the pairs plot (or not)
`serialAxesArgs`	additional arguments to modify the 'l_serialaxes' states
`color`	vector with line colors. Default is given by `l_getOption("color")`.
`group`	only used for layers. As we scroll the bar, the layers are re-calculated. This argument is used to specify which state is used to set groups (i.e. "color", "linewidth", etc).
`start`	projection to start at, if not specified, uses default associated with tour path
`parent`	a valid Tk parent widget path. When the parent widget is specified (i.e. not `NULL`) then the plot widget needs to be placed using some geometry manager like `tkpack` or `tkplace` in order to be displayed. See the examples below.
`span`	How many column/row occupies for each widget
`envir`	the `environment` to use.
`...`	named arguments to modify the serialaxes states or layouts, see details.

an l_tour_compound object that one can query the loon states and a matrix projection vectors

l_pairs, l_tour

if(interactive() && requireNamespace('tourr')) {
  # q is a `l_pairs` object
  q <- l_tour_pairs(olive[, -c(1:2)],
                    color = olive$region)
  # query the matrix of projection vectors
  proj <- q["projection"]

  # query the `l_compound` widget
  lc <- l_getPlots(q)
  # pack the `density2d` layers
  layer_pack <- lapply(lc, function(w) l_layer_density2d(w))

  #### set `as.l_tour = FALSE`
  # q is a `l_pairs` object
  q <- l_tour_pairs(tourr::flea[, 1:6],
                    as.l_tour = FALSE,
                    color = tourr::flea$species,
                    showHistogram = TRUE,
                    showSerialAxes = TRUE)

  # proj <- q["projection"] # Return a list of `NA`
  # query estimated matrix of projection vectors
  proj <- l_getProjection(q, tourr::flea[, 1:6])
}