biscale implements a set of functions for bivariate thematic mapping based on the tutorial written by Timo Grossenbacher and Angelo Zehr as well as a set of bivariate mapping palettes, including Joshua Stevens’ classic color schemes. In addition to support for two-by-two, three-by-three, and four-by-four maps, the package also supports a range of methods for calculating breaks for bivariate maps.

What’s New in v1.0.0?

New Features

• bi_class() now accepts factors for one or both of the x and y variables, allowing more flexibility for how breaks are calculated. If you want finer grained control over your categories, calculate them ahead of time and then pass the factors on to bi_class().
• bi_pal(), bi_legend(), bi_scale_fill(), and bi_scale_color() functions all support four-by-four bivariate maps when dim = 4. Note that the original five palettes do not support four-by-four mapping, but very close approximations (e.g. DkBlue2 instead of DkBlue) are now provided in their place. The legacy palettes are all still included in the package.
• The number of built-in palettes has been greatly expanded!
• Palettes can now be flipped and rotated (or both!), so that each built-in palette can be displayed in four different configurations. This includes the built-in palettes and any custom palettes that are four-by-four or smaller. If you want to flip or rotate larger palettes, you should make those decisions while creating the palette itself.
• The workflow for allowing custom palettes has been overhauled to simply the process - users can provide a named vector for the pal arguments in the bi_pal(), bi_legend(), bi_scale_fill(), and bi_scale_color() functions. All of these functions will validate your input to ensure that it maps correctly.
• bi_class() can be used to calculate bivariate breaks for maps larger than four-by-four, though it will return a warning reminding you that these maps are hard to read and that biscale does not provide palettes for larger maps. Instead, you should provide a custom palette.
• bi_class_breaks() can be used with bi_legend() to facilitate optionally adding break values to your legends. Like bi_class(), this new function accepts both continuous and pre-made factors.

Breaking Changes

• R version 3.4 is no longer supported - please use at least R version 3.5
• There is no default supplied for bi_class()’s style argument since bi_class() now accepts factors as well. Users that relied on the default behavior of bi_class() will now receive an error asking you to specify a style for calculating breaks.

Deprecated Functions

• bi_pal_manual() now returns a warning that it has been deprecated and will be removed in a later release of biscale (planned for the end of 2022). Please update your workflows to use the new approach to generating custom palettes.

Internal Improvements

• sf is now a suggested package instead of an imported package, and several dependencies have been removed in the process of re-factoring all of the code in biscale.

Documentation Improvements

• Documentation updates have been made, including the addition of a number of new examples and vignettes. These include detailed articles on bivariate palettes, working with breaks and legends, and creating bivariate maps with raster data.

What’s New in the Development Version (v1.1.0.9000)?

These require the development version to be installed using remotes::install_github(), described in the next section.

New Features

• The bi_legend() function now has a base_family argument, which can be paired with the suggested showtext package to display non-Latin characters. See the “Options for Breaks and Legends” vignette for details on using this new feature.

Installation

The easiest way to get biscale is to install it from CRAN:

install.packages("biscale")

Alternatively, the development version of biscale can be accessed from GitHub with remotes:

# install.packages("remotes")
remotes::install_github("chris-prener/biscale")

Additional details, including some tips for installing suggested dependencies, can be found in the Get started article.

Resources

In addition to instructions for installation, the main Get started article has:

• a quick overview of bivariate mapping,
• a description of the workflow for creating bivariate maps,
• a comparison of different approaches to calculating those classes,
• and a quick overview for creating legends.

There are also additional vignettes included that give an overview of palettes included in the package and working with custom palettes as well as additional advanced options for creating breaks and legends.