Nothing
# Condition 4: Undirected events with types, tie-oriented model with active riskset
# Small edgelist
edgelist <- data.frame(
time = 1:5,
actor1 = c(1, 1, 2, 2, 3),
actor2 = c(2, 3, 1, 3, 2)
)
event_types <- c(1, 1, 2, 2, 1)
# Actor info
info <- data.frame(
name = 1:3,
time = rep(0, 3),
x1 = c(10, 20, 30),
x2 = c(0, 1, 1)
)
info2 <- data.frame(
name = 1:3,
time = rep(3, 3),
x1 = c(100, 200, 300),
x2 = c(1, 1, 0)
)
info <- rbind(info, info2)
# Statistics
edgelist$type <- event_types
reh <- remify::remify(edgelist, model = "tie", directed = FALSE, riskset = "active")
effects <- ~ average(variable = "x1") + difference(variable = "x1") +
maximum(variable = "x1") + minimum(variable = "x1") +
same(variable = "x2")
stats <- remstats(reh, tie_effects = effects, attr_actors = info)
riskset <- attr(stats, "riskset")
# Baseline
expect_equal(stats[, , "baseline"], matrix(1, nrow = nrow(edgelist), ncol = nrow(riskset)))
# average
average <- rbind(
c(15, 20, 25, 15, 25),
c(15, 20, 25, 15, 25),
c(150, 200, 250, 150, 250),
c(150, 200, 250, 150, 250),
c(150, 200, 250, 150, 250)
)
expect_equal(stats[, , "average_x1"], average)
# difference
difference <- rbind(
c(10, 20, 10, 10, 10),
c(10, 20, 10, 10, 10),
c(100, 200, 100, 100, 100),
c(100, 200, 100, 100, 100),
c(100, 200, 100, 100, 100)
)
expect_equal(stats[, , "difference_x1"], difference)
# maximum
maximum <- rbind(
c(20, 30, 30, 20, 30),
c(20, 30, 30, 20, 30),
c(200, 300, 300, 200, 300),
c(200, 300, 300, 200, 300),
c(200, 300, 300, 200, 300)
)
expect_equal(stats[, , "maximum_x1"], maximum)
# minimum
minimum <- rbind(
c(10, 10, 20, 10, 20),
c(10, 10, 20, 10, 20),
c(100, 100, 200, 100, 200),
c(100, 100, 200, 100, 200),
c(100, 100, 200, 100, 200)
)
expect_equal(stats[, , "minimum_x1"], minimum)
# same
same <- rbind(
c(0, 0, 1, 0, 1),
c(0, 0, 1, 0, 1),
c(1, 0, 0, 1, 0),
c(1, 0, 0, 1, 0),
c(1, 0, 0, 1, 0)
)
expect_equal(stats[, , "same_x2"], same)
# test standardization
std_effects <- ~
average(variable = "x1", scaling = "std") +
difference(variable = "x1", scaling = "std") +
maximum(variable = "x1", scaling = "std") +
minimum(variable = "x1", scaling = "std")
std_stats <- remstats(reh, tie_effects = std_effects, attr_actors = info)
sapply(2:dim(std_stats)[3], function(p) {
stat_name <- dimnames(std_stats)[[3]][p]
scaled_original <- t(apply(stats[,,stat_name], 1, scale))
scaled_original[which(apply(stats[,,stat_name], 1, sd) == 0),] <-
rep(0, ncol(stats))
expect_equal(std_stats[,,stat_name], scaled_original)
})
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