| 1 | context("Check that computeFilaments behaves as expected") |
| 2 | |
| 3 | getDataTest = function(n, shift) |
| 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 | series = list() |
| 15 | for (i in seq_len(n)) |
| 16 | { |
| 17 | index = (i%%3) + 1 |
| 18 | level = mean(s[[index]]) |
| 19 | serie = s[[index]] - level + rnorm(L,sd=0.05) |
| 20 | # 10 series with NAs for index 2 |
| 21 | if (index == 2 && i >= 60 && i<= 90) |
| 22 | serie[sample(seq_len(L),1)] = NA |
| 23 | series[[i]] = list("level"=level,"serie"=serie) #no need for more |
| 24 | } |
| 25 | if (shift) |
| 26 | { |
| 27 | # Simulate shift at origin when predict_at > 0 |
| 28 | series[2:(n+1)] = series[1:n] |
| 29 | series[[1]] = list("level"=0, "serie"=s[[1]][1:(L%/%2)]) |
| 30 | } |
| 31 | new("Data", data=series) |
| 32 | } |
| 33 | |
| 34 | test_that("output is as expected on simulated series", |
| 35 | { |
| 36 | data = getDataTest(150, FALSE) |
| 37 | |
| 38 | # index 142 : serie type 2 |
| 39 | f = computeFilaments(data, 142, limit=60, plot=FALSE) |
| 40 | # Expected output: 22 series of type 3 (closer), then 50-2-10 series of type 2 |
| 41 | expect_identical(length(f$indices), 60) |
| 42 | expect_identical(length(f$colors), 60) |
| 43 | for (i in 1:22) |
| 44 | { |
| 45 | expect_identical((f$indices[i] %% 3) + 1, 3) |
| 46 | expect_match(f2$colors[i], f$colors[1]) |
| 47 | } |
| 48 | for (i in 23:60) |
| 49 | { |
| 50 | expect_identical((f$indices[i] %% 3) + 1, 2) |
| 51 | expect_match(f2$colors[i], f$colors[23]) |
| 52 | } |
| 53 | expect_match(colors[1], "...") |
| 54 | expect_match(colors[23], "...") |
| 55 | }) |
| 56 | |
| 57 | test_that("output is as expected on simulated series", |
| 58 | { |
| 59 | data = getDataTest(150, TRUE) |
| 60 | |
| 61 | # index 143 : serie type 3 |
| 62 | f = computeFilaments(data, 143, limit=70, plot=FALSE) |
| 63 | # Expected output: 22 series of type 2 (closer) then 50-2 series of type 3 |
| 64 | expect_identical(length(f$indices), 70) |
| 65 | expect_identical(length(f$colors), 70) |
| 66 | for (i in 1:22) |
| 67 | { |
| 68 | # -1 because of the initial shift |
| 69 | expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 2) |
| 70 | expect_match(f$colors[i], f$colors[1]) |
| 71 | } |
| 72 | for (i in 23:70) |
| 73 | { |
| 74 | expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 3) |
| 75 | expect_match(f$colors[i], f$colors[23]) |
| 76 | } |
| 77 | expect_match(colors[1], "...") |
| 78 | expect_match(colors[23], "...") |
| 79 | }) |
| 80 | |
| 81 | test_that("output is as expected on simulated series", |
| 82 | { |
| 83 | data = getDataTest(150, TRUE) |
| 84 | |
| 85 | # index 144 : serie type 1 |
| 86 | f = computeFilaments(data, 144, limit=50, plot=FALSE) |
| 87 | # Expected output: 2 series of type 3 (closer), then 50-2 series of type 1 |
| 88 | expect_identical(length(f$indices), 50) |
| 89 | expect_identical(length(f$colors), 50) |
| 90 | for (i in 1:2) |
| 91 | { |
| 92 | # -1 because of the initial shift |
| 93 | expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 3) |
| 94 | expect_match(f$colors[i], f$colors[1]) |
| 95 | } |
| 96 | for (i in 3:50) |
| 97 | { |
| 98 | expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 1) |
| 99 | expect_match(f$colors[i], f$colors[3]) |
| 100 | } |
| 101 | expect_match(colors[1], "...") |
| 102 | expect_match(colors[3], "...") |
| 103 | }) |