View source: R/colorize_node_attrs.R
colorize_node_attrs | R Documentation |
Within a graph's internal node data frame (ndf), use a categorical node attribute to generate a new node attribute with color values.
colorize_node_attrs(
graph,
node_attr_from,
node_attr_to,
cut_points = NULL,
palette = "Spectral",
alpha = NULL,
reverse_palette = FALSE,
default_color = "#D9D9D9"
)
graph |
A graph object of class |
node_attr_from |
The name of the node attribute column from which color values will be based. |
node_attr_to |
The name of the new node 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., |
alpha |
An optional alpha transparency value to apply to the generated
colors. Should be in the range of |
reverse_palette |
An option to reverse the order of colors in the chosen
palette. The default is |
default_color |
A hexadecimal color value to use for instances when the
values do not fall into the bucket ranges specified in the |
A graph object of class dgr_graph
.
Other node creation and removal:
add_n_node_clones()
,
add_n_nodes()
,
add_n_nodes_ws()
,
add_node()
,
add_node_clones_ws()
,
add_node_df()
,
add_nodes_from_df_cols()
,
add_nodes_from_table()
,
copy_node_attrs()
,
create_node_df()
,
delete_node()
,
delete_nodes_ws()
,
drop_node_attrs()
,
join_node_attrs()
,
layout_nodes_w_string()
,
mutate_node_attrs()
,
mutate_node_attrs_ws()
,
node_data()
,
recode_node_attrs()
,
rename_node_attrs()
,
rescale_node_attrs()
,
set_node_attr_to_display()
,
set_node_attr_w_fcn()
,
set_node_attrs()
,
set_node_attrs_ws()
,
set_node_position()
# Create a graph with 8
# nodes and 7 edges
graph <-
create_graph() %>%
add_path(n = 8) %>%
set_node_attrs(
node_attr = weight,
values = c(
8.2, 3.7, 6.3, 9.2,
1.6, 2.5, 7.2, 5.4))
# Find group membership values for all nodes
# in the graph through the Walktrap community
# finding algorithm and join those group values
# to the graph's internal node data frame (ndf)
# with the `join_node_attrs()` function
graph <-
graph %>%
join_node_attrs(
df = get_cmty_walktrap(.))
# Inspect the number of distinct communities
graph %>%
get_node_attrs(
node_attr = walktrap_group) %>%
unique() %>%
sort()
# Visually distinguish the nodes in the different
# communities by applying colors using the
# `colorize_node_attrs()` function; specifically,
# set different `fillcolor` values with an alpha
# value of 90 and apply opaque colors to the node
# border (with the `color` node attribute)
graph <-
graph %>%
colorize_node_attrs(
node_attr_from = walktrap_group,
node_attr_to = fillcolor,
palette = "Greens",
alpha = 90) %>%
colorize_node_attrs(
node_attr_from = walktrap_group,
node_attr_to = color,
palette = "viridis",
alpha = 80)
# Show the graph's internal node data frame
graph %>% get_node_df()
# Create a graph with 8 nodes and 7 edges
graph <-
create_graph() %>%
add_path(n = 8) %>%
set_node_attrs(
node_attr = weight,
values = c(
8.2, 3.7, 6.3, 9.2,
1.6, 2.5, 7.2, 5.4))
# We can bucketize values in `weight` using
# `cut_points` and 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_node_attrs(
node_attr_from = weight,
node_attr_to = fillcolor,
cut_points = c(1, 3, 5, 7, 9))
# Now there will be a `fillcolor` node attribute
# with distinct colors (the `#D9D9D9` color is
# the default `gray85` color)
graph %>% get_node_df()
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