context("test feature-set: DISTANCE")
test_that("getDistanceFeatureSet does produce reasonable results", {
# build this simple network object by hand
x = generateSimpleTestNetwork()
# "should be" values
mst_dists_sum.expected = (getNumberOfNodes(x) - 1L) / sum(x$distance.matrix)
# build feature set and check structure
feature.set = getDistanceFeatureSet(x)
expect_feature_list(feature.set, feature.set = "DISTANCE")
# check if values are correct
# we have 4 times distance 1 and 2 times distance sqrt(2)
expect_true((feature.set$fraction_of_distinct_distances - 2 / 6) < 0.001)
expect_true((feature.set$fraction_shorter_mean_distance - 4 / 6) < 0.001)
# see comment above. Distance 1 is the mode.
expect_equal(feature.set$mode_quantity, 1L)
# ... and there are 4 edges with this edge costs
expect_equal(feature.set$mode_frequency, 4L)
# Since there is one mode, the value of the mode corresponds to the mode mean
expect_equal(feature.set$mode_mean, 1)
# the 4 lowest edge values correspond to the mode
expect_equal(feature.set$sum_of_lowest_edge_values, 4)
})
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