Nothing

```
context("Community detection algorithms")
test_that("the edge betweeness algorithm is functional", {
# Create a random graph
graph <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 10,
set_seed = 23)
# Get the edge betweenness for the graph
edge_betweeness <- get_cmty_edge_btwns(graph)
# Expect that a `data.frame` object is returned
expect_is(
edge_betweeness, "data.frame")
# Expect 2 columns in the data frame
expect_equal(
ncol(
edge_betweeness), 2)
# Expect specific column names in this data frame
expect_equal(
colnames(edge_betweeness),
c("id", "edge_btwns_group"))
# Expect as many rows in the data frame as there
# are nodes in the graph
expect_equal(
nrow(edge_betweeness),
count_nodes(graph = graph))
# For this analysis expect 5 different groups
expect_equal(
sort(unique(edge_betweeness$edge_btwns_group)),
c(1, 2, 3, 4, 5, 6))
# Expect the first column to be integer
expect_is(
edge_betweeness$id, "integer")
# Expect the second column to be numeric
expect_is(
edge_betweeness$edge_btwns_group, "numeric")
})
test_that("the fast-greedy algorithm is functional", {
# Create a random graph
graph <-
create_graph() %>%
add_gnm_graph(
n = 15,
m = 10,
set_seed = 23)
# Get the edge betweenness for the graph
fast_greedy <- get_cmty_fast_greedy(graph)
# Expect that a `data.frame` object is returned
expect_is(
fast_greedy, "data.frame")
# Expect 2 columns in the data frame
expect_equal(
ncol(fast_greedy), 2)
# Expect specific column names in this data frame
expect_equal(
colnames(fast_greedy),
c("id", "f_g_group"))
# Expect as many rows in the data frame as there
# are nodes in the graph
expect_equal(
nrow(fast_greedy), count_nodes(graph = graph))
# For this analysis expect two different groups
# identified with labels `1` and `2`
expect_equal(
sort(unique(fast_greedy$f_g_group)),
c(1, 2, 3, 4, 5, 6))
# Expect the first column to be integer
expect_is(
fast_greedy$id, "integer")
# Expect the second column to be numeric
expect_is(
fast_greedy$f_g_group, "numeric")
})
test_that("the leading eigenvector algorithm is functional", {
# Create a random graph
graph <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 10,
set_seed = 23)
# Get the edge betweenness for the graph
l_eigenvec <- get_cmty_l_eigenvec(graph)
# Expect that a `data.frame` object is returned
expect_is(
l_eigenvec, "data.frame")
# Expect 2 columns in the data frame
expect_equal(
ncol(l_eigenvec), 2)
# Expect specific column names in this data frame
expect_equal(
colnames(l_eigenvec),
c("id", "l_eigenvec_group"))
# Expect as many rows in the data frame as there
# are nodes in the graph
expect_equal(
nrow(l_eigenvec), count_nodes(graph = graph))
# For this analysis expect two different groups
# identified with labels `1` and `2`
expect_equal(
sort(unique(l_eigenvec$l_eigenvec_group)),
c(1, 2, 3, 4))
# Expect the first column to be integer
expect_is(
l_eigenvec$id, "integer")
# Expect the second column to be numeric
expect_is(l_eigenvec$l_eigenvec_group, "numeric")
})
test_that("the Louvain algorithm is functional", {
# Create a random graph
graph <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 10,
set_seed = 23)
# Get the edge betweenness for the graph
louvain <- get_cmty_louvain(graph)
# Expect that a `data.frame` object is returned
expect_is(
louvain, "data.frame")
# Expect 2 columns in the data frame
expect_equal(
ncol(louvain), 2)
# Expect specific column names in this data frame
expect_equal(
colnames(louvain),
c("id", "louvain_group"))
# Expect as many rows in the data frame as there
# are nodes in the graph
expect_equal(
nrow(louvain), count_nodes(graph = graph))
# For this analysis expect two different groups
# identified with labels `1` and `2`
expect_equal(
sort(unique(louvain$louvain_group)),
c(1, 2, 3, 4))
# Expect the first column to be integer
expect_is(
louvain$id, "integer")
# Expect the second column to be numeric
expect_is(
louvain$louvain_group, "numeric")
})
test_that("the walktrap algorithm is functional", {
# Create a random graph
graph <-
create_graph() %>%
add_gnm_graph(
n = 10,
m = 10,
set_seed = 23)
# Get the edge betweenness for the graph
walktrap <- get_cmty_walktrap(graph)
# Expect that a `data.frame` object is returned
expect_is(
walktrap, "data.frame")
# Expect 2 columns in the data frame
expect_equal(
ncol(walktrap), 2)
# Expect specific column names in this data frame
expect_equal(
colnames(walktrap),
c("id", "walktrap_group"))
# Expect as many rows in the data frame as there
# are nodes in the graph
expect_equal(
nrow(walktrap), count_nodes(graph = graph))
# For this analysis expect two different groups
# identified with labels `1` and `2`
expect_equal(
sort(unique(walktrap$walktrap_group)),
c(1, 2, 3, 4))
# Expect the first column to be integer
expect_is(
walktrap$id, "integer")
# Expect the second column to be numeric
expect_is(
walktrap$walktrap_group, "numeric")
})
```

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