Nothing
## ------------------------------------------------------------------------
suppressPackageStartupMessages(library("dplyr")) # for tidy data manipulations
suppressPackageStartupMessages(library("magrittr")) # for friendly piping
suppressPackageStartupMessages(library("network")) # for plotting
suppressPackageStartupMessages(library("sna")) # for plotting
suppressPackageStartupMessages(library("statnet.common")) # for plotting
suppressPackageStartupMessages(library("networkD3")) # for plotting
suppressPackageStartupMessages(library("igraph")) # for graph computations
suppressPackageStartupMessages(library("pkggraph")) # attach the package
suppressMessages(init(local = TRUE)) # initiate the package
## ---- eval = TRUE--------------------------------------------------------
get_neighborhood("mlr") # a tibble, every row indicates a dependency
# observe only 'Imports' and reverse 'Imports'
neighborhood_graph("mlr", relation = "Imports") %>%
plot()
# observe the neighborhood of 'tidytext' package
get_neighborhood("tidytext") %>%
make_neighborhood_graph() %>%
plot()
# interact with the neighborhood of 'tm' package
# legend does not appear in the vignette, but it appears directly
neighborhood_graph("tm") %>%
plotd3(700, 700)
# which packages work as 'hubs' or 'authorities' in the above graph
neighborhood_graph("tidytext", type = "igraph") %>%
extract2(1) %>%
authority_score() %>%
extract2("vector") %>%
tibble(package = names(.), score = .) %>%
top_n(10, score) %>%
ggplot(aes(reorder(package, score), score)) +
geom_bar(stat = "identity") +
xlab("package") +
ylab("score") +
coord_flip()
## ---- eval = TRUE--------------------------------------------------------
get_imports(c("dplyr", "tidyr"))
## ---- eval = FALSE-------------------------------------------------------
# library("pkggraph")
# init(local = FALSE)
## ---- eval = TRUE--------------------------------------------------------
get_imports("ggplot2")
## ---- eval = TRUE--------------------------------------------------------
get_reverse_suggests("knitr", level = 1)
## ------------------------------------------------------------------------
get_reverse_suggests("knitr", level = 2)
## ------------------------------------------------------------------------
get_all_dependencies("mlr", relation = c("Depends", "Imports"))
get_all_dependencies("mlr", relation = c("Depends", "Imports"), level = 2)
## ---- eval = TRUE--------------------------------------------------------
get_all_dependencies("mlr"
, relation = c("Depends", "Imports")
, level = 2
, strict = TRUE)
## ---- eval = TRUE--------------------------------------------------------
get_neighborhood("hash", level = 2)
get_neighborhood("hash", level = 2) %>%
make_neighborhood_graph %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
get_neighborhood("hash"
, level = 2
, relation = c("Imports", "Depends")
, strict = TRUE) %>%
make_neighborhood_graph %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
get_neighborhood("mlr", relation = "Imports") %>%
make_neighborhood_graph() %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
get_neighborhood("mlr", relation = "Imports", interconnect = FALSE) %>%
make_neighborhood_graph() %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
neighborhood_graph("caret", relation = "Imports") %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
get_all_reverse_dependencies("rpart", relation = "Imports") %>%
make_neighborhood_graph() %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
"dplyr" %imports% "tibble"
## ---- eval = TRUE--------------------------------------------------------
relies("glmnet")[[1]]
# level 1 dependencies of "glmnet" are:
get_all_dependencies("glmnet", relation = c("Imports", "Depends", "LinkingTo"))[[3]]
"glmnet" %relies% "grid"
reverse_relies("tokenizers")[[1]]
## ---- eval = TRUE--------------------------------------------------------
pkggraph::neighborhood_graph("hash") %>%
plot()
## ---- eval = TRUE--------------------------------------------------------
pkggraph::neighborhood_graph("hash") %>%
plot(nodeImportance = "in", background = "white")
## ---- eval = TRUE--------------------------------------------------------
pkggraph::neighborhood_graph("hash") %>%
plot(nodeImportance = "none", background = "white")
## ---- eval = TRUE--------------------------------------------------------
# legend does not appear in the vignette, but it appears directly
plotd3(neighborhood_graph("tibble"), height = 1000, width = 1000)
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