# Create a random graph using the
# `add_gnm_graph()` function
graph <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 7,
set_seed = 23) %>%
set_edge_attrs(
edge_attr = weight,
values = rnorm(
n = count_edges(.),
mean = 5,
sd = 1))
# Get the graph's internal edf
# to show which edge attributes
# are available
graph %>% get_edge_df()
# Rescale the `weight` edge
# attribute, so that its values
# are rescaled between 0 and 1
graph <-
graph %>%
rescale_edge_attrs(
edge_attr_from = weight,
to_lower_bound = 0,
to_upper_bound = 1)
# Get the graph's internal edf
# to show that the edge attribute
# values had been rescaled
graph %>% get_edge_df()
# Scale the values in the `weight`
# edge attribute to different
# shades of gray for the `color`
# edge attribute and different
# numerical values for the
# `penwidth` attribute
graph <-
graph %>%
rescale_edge_attrs(
edge_attr_from = weight,
to_lower_bound = "gray80",
to_upper_bound = "gray20",
edge_attr_to = color) %>%
rescale_edge_attrs(
edge_attr_from = weight,
to_lower_bound = 0.5,
to_upper_bound = 3,
edge_attr_to = penwidth)
# Get the graph's internal edf
# once more to show that scaled
# grayscale colors are now available
# in `color` and scaled numerical
# values are in the `penwidth`
# edge attribute
graph %>% get_edge_df()
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