# Create a random graph using the
# `add_gnm_graph()` function
graph <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 15,
set_seed = 23)
# Obtain Jaccard similarity
# values for each pair of
# nodes as a square matrix
j_sim_matrix <-
graph %>%
get_jaccard_similarity()
# Create a weighted, undirected
# graph from the resultant matrix
# (effectively treating that
# matrix as an adjacency matrix)
graph <-
j_sim_matrix %>%
from_adj_matrix(weighted = TRUE)
# The graph in this case is a fully connected graph
# with loops, where jaccard similarity values are
# assigned as edge weights (edge attribute `weight`);
# The minimum spanning tree for this graph is the
# connected subgraph where the edges retained have
# the lowest similarity values possible
min_spanning_tree_graph <-
graph %>%
transform_to_min_spanning_tree() %>%
copy_edge_attrs(
edge_attr_from = weight,
edge_attr_to = label) %>%
set_edge_attrs(
edge_attr = fontname,
values = "Helvetica") %>%
set_edge_attrs(
edge_attr = color,
values = "gray85") %>%
rescale_edge_attrs(
edge_attr_from = weight,
to_lower_bound = 0.5,
to_upper_bound = 4.0,
edge_attr_to = penwidth)
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