summarytrees_htmlwidget 怼烎@ 2022-09-21 13:08 3阅读 0赞 **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. We can see some early [examples][] with `plotly` from early adopter [Andrew Clark @pssguy][Andrew Clark _pssguy]. ## This Week’s Widget - summarytrees\_htmlwidget ## [Kenneth Shirley][] and Howard Karloff authored an interesting [paper][]. > (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 `R` package [`summarytrees`][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 [`stmBrowser`][stmBrowser] and [`stmCorrViz`][stmCorrViz], I thought `summarytrees` would also be a great candidate for an `htmlwidget`. This is a work in progress. Please offer feedback and ideas on this Github [issue][]. ## Installation ## This is not on CRAN and only exists in a `summarytrees` fork, so to install we will need some help from `devtools::install_github`. devtools::install_github("timelyportfolio/summarytrees@htmlwidget") ## Examples ## # 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) ## [1] "Running order.nodes() function to prepare data" ## [1] " Computing node levels" ## [1] " Computing child indices for each parent" ## [1] "Running C function to compute summary trees" ## [1] "Computation finished; now formatting output" ## Thanks ## Thanks [Kenneth Shirley][] for the research and implementation of `summarytrees`. As always, thanks to [issue 86]: https://github.com/ramnathv/htmlwidgets/issues/86#issuecomment-159863989 [examples]: https://mytinyshinys.shinyapps.io/premierLeague [Andrew Clark _pssguy]: https://twitter.com/pssguy [Kenneth Shirley]: http://www.kennyshirley.com/ [paper]: https://scholar.google.com/scholar?cluster=11439479883993290700&hl=en&as_sdt=0,1 [summarytrees]: https://github.com/kshirley/summarytrees [presentation at JSM 2015]: https://www.amstat.org/meetings/jsm/2015/onlineprogram/AbstractDetails.cfm?abstractid=314588 [stmBrowser]: http://www.buildingwidgets.com/blog/2015/4/2/week-13-interactive-stm [stmCorrViz]: http://www.buildingwidgets.com/blog/2015/12/1/week-48-stmcorrviz [issue]: https://github.com/kshirley/summarytrees/issues/1
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