| 1 | context("Check that computeFilaments behaves as expected") |
| 2 | |
| 3 | test_that("output is as expected on simulated series", |
| 4 | { |
| 5 | x = seq(0,10,0.1) |
| 6 | L = length(x) |
| 7 | s1 = cos(x) |
| 8 | s2 = sin(x) |
| 9 | s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] ) |
| 10 | #sum((s1-s2)^2) == 97.59381 |
| 11 | #sum((s1-s3)^2) == 57.03051 |
| 12 | #sum((s2-s3)^2) == 40.5633 |
| 13 | s = list( s1, s2, s3 ) |
| 14 | n = 150 |
| 15 | series = list() |
| 16 | for (i in seq_len(n)) |
| 17 | { |
| 18 | index = (i%%3) + 1 |
| 19 | level = mean(s[[index]]) |
| 20 | serie = s[[index]] - level + rnorm(L,sd=0.05) |
| 21 | # 10 series with NAs for index 2 |
| 22 | if (index == 2 && i >= 60 && i<= 90) |
| 23 | serie[sample(seq_len(L),1)] = NA |
| 24 | series[[i]] = list("level"=level,"serie"=serie) #no need for more |
| 25 | } |
| 26 | data = new("Data", data=series) |
| 27 | |
| 28 | # index 142 : serie type 2 |
| 29 | f2 = computeFilaments(data, 142, limit=60, plot=FALSE) |
| 30 | # Expected output: 22 series of type 3 (closer), then 50-2-10 series of type 2 |
| 31 | # |
| 32 | # |
| 33 | # |
| 34 | # |
| 35 | # |
| 36 | # |
| 37 | # Simulate shift at origin when predict_at > 0 |
| 38 | series[2:(n+1)] = series[1:n] |
| 39 | series[[1]] = list("level"=0, "serie"=s[[1]][1:(L%/%2)]) |
| 40 | # index 143 : serie type 3 |
| 41 | f3 = computeFilaments(data, 143, limit=70, plot=FALSE) |
| 42 | # Expected output: 22 series of type 2 (closer) then 50-2 series of type 3 |
| 43 | # ATTENTION au shift |
| 44 | # |
| 45 | # |
| 46 | # index 144 : serie type 1 |
| 47 | f1 = computeFilaments(data, 144, limit=50, plot=FALSE) |
| 48 | # Expected output: 2 series of type 3 (closer), then 50-2 series of type 1 |
| 49 | # |
| 50 | expect_that( diff_norm, is_less_than(0.5) ) |
| 51 | }) |