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Prop Type: Accessor

Source: R/doc-proptypes.R
accessor.Rd

Accessors map data columns to visual representations, primarily:

  • colours: fill, line, highlight

  • sizes: radius, elevation, width, height

  • geometries point/multipoint, linestring/multilinestring, polygon/multipolygon

On the client, an accessor is translated to a javascript function that retrieves the specified column values for each rendered feature. An equivalent R function would look something like function(data, col, index) data[[index, col]].

Tidy-eval

Accessors support tidy-eval expressions. Rules for referencing a column vs. a value from the environment is similar to dplyr::mutate(), with the main difference being that all names are assumed to be columns of data, not falling back to the environment when they're not found.

Like dplyr::mutate(), using string literals to reference columns isn't supported – this will be interpreted as a literal string. You may reference a column with:

  • a name (e.g. my_col)

  • a call evaluating name, e.g. as.name(), rlang::sym(), etc

  • by injecting a variable from the environment containing a name with !!my_var, or {{myvar}}

Literal expressions – except calls evaluating a name or a scale – will be interpreted as constant values (e.g. "#ff0000", 1, TRUE, etc.). To use the value of a variable from the environment, use the injection operators, e.g. !!my_constant.

Examples:

  • get_fill_color = color: column accessor, referencing the "color" column

  • get_fill_color = "#ff0000": a constant value (red)

  • get_fill_color = !!color: injects the value of color from the environment; if it's a name it will be a column with the value of color (e.g. color <- as.name("my_color_column"))

  • get_fill_color = rlang::sym("my_color"): column accessor, referencing "my_color" column

  • get_fill_color = scale_color_threshold(color): a threshold scale, which transforms the "color" column

Accessors vs. Scales

Some parameters accept either an accessor or a scale. Scales transform numeric and categorical vectors into colours and numeric values, and optionally render a legend; similar to ggplot scaling aesthetics.

An accessor can perform this same task by manually transforming some input into a vector of colours or numbers, but this is worse because:

  • the transformed output (e.g. a colour vector) must be stored in the data (data bloat)

  • visual representations aren't data

  • legend won't be rendered

Accessors vs. Values

Some parameters accept either an accessor or a value; get_radius is such an example which accepts either a scalar numeric value, or an accessor to a numeric column, or a numeric scale. A value can be thought of as accessor where all values in the referenced column are the same (i.e. a constant column), but optimised for file size and render speed.