Methods to calculate indices of diversity on numerical matrices based on information theory. The rationale behind the package is described in Rocchini, Marcantonio and Ricotta (2017) <doi:10.1016/j.ecolind.2016.07.039> and Rocchini, Marcantonio,..., Ricotta (2021) <doi:10.1101/2021.01.23.427872>.

Provides R functions to selectively rasterize components
of 'grid' output.

Easily and Rapidly Generate Raster Image Data with Support for
'Plotly.js'
c(person("Zehao", "Xu", role = c("aut", "cre"), email = "z267xu@uwaterloo.ca"), person("Ryan Patrick", "Kyle", role = c("ctb"), comment = c(ORCID = "0000-0001-5829-9867"), email = "ryan@plot.ly"), person(family = "Plotly Technologies", role = "cph"))
Easily and rapidly generate raster data in R, even for very large datasets, with an aesthetics-based mapping syntax that should be familiar to users of the 'ggplot2' package. While 'rasterly' does not attempt to reproduce the full functionality of the 'Datashader' graphics pipeline system for Python, the 'rasterly' API has several core elements in common with that software package.
data.table, rlang, plotly, ggplot2, magrittr
grid, stats, compiler, loon, purrr, covr, testthat, knitr,
rmarkdown, lubridate
Zehao Xu [aut, cre],
Ryan Patrick Kyle [ctb] (<https://orcid.org/0000-0001-5829-9867>),
Plotly Technologies [cph]

It aims to easily and rapidly generate raster data in R, even for very large datasets, with an aesthetics-based mapping syntax that should be familiar to users of the 'ggplot2' package. While 'rasterly' does not attempt to reproduce the full functionality of the 'Datashader' graphics pipeline system for Python, the 'rasterly' API has several core elements in common with that software package.
data.table, rlang, plotly, ggplot2, magrittr, grid, stats
covr, testthat, knitr, rmarkdown, lubridate

person(given = "Ilari",
family = "Scheinin",
role = c("aut", "cre"),
email = "ilari.scheinin+rasterpdf@gmail.com",
comment = c(ORCID = "0000-0002-4696-9066"))
The ability to plot raster graphics in PDF files can be useful
when one needs multi-page documents, but the plots contain so many
individual elements that (the usual) use of vector graphics results in
inconveniently large file sizes. Internally, the package plots each
individual page as a PNG, and then combines them in one PDF file.
Ilari Scheinin [aut, cre] (<https://orcid.org/0000-0002-4696-9066>)