DiagrammeR (version 0.9.0)

colorize_edge_attrs: Apply colors based on edge attribute values

Description

Within a graph's internal edge data frame (edf), use a categorical edge attribute to generate a new edge attribute with color values.

Usage

colorize_edge_attrs(graph, edge_attr_from, edge_attr_to, cut_points = NULL,
  palette = "Spectral", alpha = NULL, reverse_palette = FALSE,
  default_color = "#D9D9D9")

Arguments

graph

a graph object of class dgr_graph.

edge_attr_from

the name of the edge attribute column from which color values will be based.

edge_attr_to

the name of the new edge attribute to which the color values will be applied.

cut_points

an optional vector of numerical breaks for bucketizing continuous numerical values available in a edge attribute column.

palette

can either be: (1) a palette name from the RColorBrewer package (e.g., Greens, OrRd, RdYlGn), (2) viridis, which indicates use of the viridis color scale from the package of the same name, or (3) a vector of hexadecimal color names.

alpha

an optional alpha transparency value to apply to the generated colors. Should be in the range of 0 (completely transparent) to 100 (completely opaque).

reverse_palette

an option to reverse the order of colors in the chosen palette. The default is FALSE.

default_color

a hexadecimal color value to use for instances when the values do not fall into the bucket ranges specified in the cut_points vector.

Value

a graph object of class dgr_graph.

Examples

# NOT RUN {
# Create a graph with 5 nodes and 4 edges
graph <-
  create_graph() %>%
  add_path(5) %>%
  set_edge_attrs(
    "weight", c(3.7, 6.3, 9.2, 1.6))

# We can bucketize values in the edge `weight`
# attribute using `cut_points` and, by doing so,
# assign colors to each of the bucketed ranges
# (for values not part of any bucket, a gray color
# is assigned by default)
graph <-
  graph %>%
  colorize_edge_attrs(
    "weight", "color",
    cut_points = c(0, 2, 4, 6, 8, 10))

# Now there will be a `color` edge attribute
# with distinct colors
get_edge_df(graph)
#>   id from to  rel weight   color
#> 1  1    1  2 <NA>    3.7 #FDAE61
#> 2  2    2  3 <NA>    6.3 #ABDDA4
#> 3  3    3  4 <NA>    9.2 #2B83BA
#> 4  4    4  5 <NA>    1.6 #D7191C
# }