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# Obtaining the minimum spanning tree of a graph
test_that("the MST algorithm is functional", {
# Create a random graph and obtain Jaccard
# similarity values for each pair of nodes
# as a square matrix
j_sim_matrix <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 22,
set_seed = 23) %>%
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()
# Expect no loops in `min_spanning_tree_graph`
expect_true(
all(get_node_info(min_spanning_tree_graph)$loops == 0))
# Expect that all nodes are connected
expect_true(
is_graph_connected(min_spanning_tree_graph))
})
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