Functions for performing polygon geometry with 'grid' grobs.
             This allows complex shapes to be defined by combining simpler
             shapes.

Functions to convert a page of plots drawn with the 
  'graphics' package into identical output drawn with the 'grid' package.
  The result looks like the original 'graphics'-based plot, but consists
  of 'grid' grobs and viewports that can then be manipulated with 
  'grid' functions (e.g., edit grobs and revisit viewports).

Functions for drawing node-and-edge graphs that have been 
              laid out by 'graphviz'.  This provides an alternative 
              rendering to that provided by the 'Rgraphviz' package, with
              two main advantages:  the rendering provided by 'gridGraphviz'
              should be more similar to what 'graphviz' itself would draw;
              and rendering with 'grid' allows for post-hoc customisations
              using the named viewports and grobs that 'gridGraphviz'
              produces.

A simple and flexible tool designed to create enriched figures and tables by providing a way to add text 
    around them through predefined or custom layouts. 
    Any input which is convertible to 'grob' is supported, like 'ggplot', 'gt' or 'flextable'. 
    Based on R 'grid' graphics, for more details see Paul Murrell (2018) <doi:10.1201/9780429422768>.

Discretize multivariate continuous data using a grid
 to capture the joint distribution that preserves clusters in
 original data. It can handle both labeled or unlabeled data.
 Both published methods (Wang et al 2020) <doi:10.1145/3388440.3412415>
 and new methods are included. Joint grid discretization
 can prepare data for model-free inference of association,
 function, or causality.

Can be used for optimal transport between two-dimensional grids with respect to separable cost functions of l^p form. It utilizes the Frank-Wolfe algorithm to approximate so-called pivot measures: One-dimensional transport plans that fully describe the full transport, see G. Auricchio (2023) <doi:10.4171/RLM/1026>. For these, it offers methods for visualization and to extract the corresponding transport plans and costs. Additionally, related functions for one-dimensional optimal transport are available.