Bleeding Edge - crosstalk
I feel obligated to mention this again. If you want to get a preview of the exciting changes for
htmlwidgets, be sure to check out
htmlwidgets issue 86. Thanks to Joe Cheng from RStudio for taking the lead on this.
This Week’s Widget - summarytrees_htmlwidget
(2013). Howard Karloff and Kenneth E. Shirley. “Maximum Entropy Summary Trees”, Computer Graphics Forum (Proc. EuroVis), Volume 32, Issue 3, Part 1, pp. 71-80.
Subsequently, Kenny made an
summarytrees to create and visualize these summary trees. I learned about the R/d3.js combination after Kenny’s presentation at JSM 2015. Similar to the
htmlwidget conversions of
stmCorrViz, I thought
summarytrees would also be a great candidate for an
This is a work in progress. Please offer feedback and ideas on this Github issue.
This is not on CRAN and only exists in a
summarytrees fork, so to install we will need some help from
# devtools::install_github("timelyportfolio/summarytrees@htmlwidget") library(summarytrees) data(dmoz) #use example from vignette K <- 100 g <- greedy(node = dmoz[, "node"], parent = dmoz[, "parent"], weight = dmoz[, "weight"], label = dmoz[, "label"], K = K) # Prepare the summary trees for visualization: json <- prepare.vis(tree.list = g$summary.trees, labels = g$data[, "label"], tree = g$tree, legend.width = 150, node.width = 225, node.height = 14, units = "# of URLs", print.weights = TRUE, legend.color = "lightsteelblue", color.level = 3) summarytrees_htmlwidget(json)
##  "Running order.nodes() function to prepare data" ##  " Computing node levels" ##  " Computing child indices for each parent" ##  "Running C function to compute summary trees" ##  "Computation finished; now formatting output"
Thanks Kenneth Shirley for the research and implementation of
As always, thanks to
- Ramnath Vaidyanathan and RStudio for
- all the contributors to