While trelliscopejs is a very powerful visualization paradigm, it can be hard to munge the data into the appropriate format. This function automatically creates a trelliscopejs visualization populated with pivot tables created by rpivotTable.

For the arguments aggregator and renderer see aggregatorName and rendererName arguments from the rpivotTable package. For all other arguments (except the data argument), see the identical arguments in the trelliscopejs package.

precise_trellis(data, path = NULL, diagnostics = NULL,
  panel_col = "panel", name = "temp", group = "common", desc = "",
  md_desc = "", height = 500, width = 500, state = NULL, nrow = 1,
  ncol = 1, jsonp = TRUE, self_contained = FALSE, thumb = FALSE)

Arguments

data	A square, numeric dataframe, matrix or tibble.
path	The base directory of the trelliscope application.
diagnostics	XYZ
panel_col	optional string specifying the column to use for panels (if there are multiple plot columns in x)
name	A string name of the display.
group	Group that the display belongs to.
desc	Optional text description of the display.
md_desc	Optional string of markdown that will be shown in the viewer for additional context about the display.
height	Height in pixels of each panel.
width	Width in pixels of each panel.
state	the initial state the display will open in
nrow	The number of rows of panels to display by default.
ncol	The number of columns of panels to display by default.
jsonp	should json for display object be jsonp (TRUE) or json (FALSE)?
self_contained	should the Trelliscope display be a self-contained html document? (see note)
thumb	should a thumbnail be created?

Value

A trellisopejs object populated by pivot tables.

References

Muchmore, B., Muchmore P. and Alarcón-Riquelme ME. (2018). Optimal Distance Matrix Construction with PreciseDist and PreciseGraph.

Enzo Martoglio (2018). rpivotTable: Build Powerful Pivot Tables and Dynamically Slice & Dice your Data. R package version 0.3.0. https://CRAN.R-project.org/package=rpivotTable

Examples

library(PreciseDist)

test_matrix <- replicate(10, rnorm(100))

test_dists <- test_matrix %>%
    precise_dist(c("manhattan", "euclidean"))
#> [1] "Starting dists calculations at 2018-11-29 15:20:29"
#> [1] "Finished dists calculations at 2018-11-29 15:20:29"
#> [1] "Calculations took: 0.54 seconds"
#> [1] "Starting dist_funcs calculations at 2018-11-29 15:20:29"
#> [1] "Finished dist_funcs calculations at 2018-11-29 15:20:30"
#> [1] "Calculations took: 0 seconds"

test_fusion <- test_dists %>%
  precise_fusion(fusion = "fuse", verbose = TRUE)
#> [1] "Starting distance matrix fusion using fuse at 2018-11-29 15:20:30"
#> [1] "Finished distance matrix fusion at 2018-11-29 15:20:30"
#> [1] "Fusion took: 0 seconds"