pkg/tests/testthat/test.computeFilaments.R

   1 context("Check that computeFilaments behaves as expected")
   2
   3 #shorthand: map 1->1, 2->2, 3->3, 4->1, ..., 149->2, 150->3
   4 I = function(i)
   5     (i-1) %% 3 + 1
   6
   7 #MOCK data; NOTE: could be in inst/testdata as well
   8 getDataTest = function(n)
   9 {
  10     data = Data$new()
  11     x = seq(0,9.5,0.1)
  12     L = length(x) #96 1/4h
  13     s1 = cos(x)
  14     s2 = sin(x)
  15     s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] )
  16     #sum((s1-s2)^2) == 96
  17     #sum((s1-s3)^2) == 58
  18     #sum((s2-s3)^2) == 38
  19     s = list(s1, s2, s3)
  20     series = list()
  21     for (i in seq_len(n))
  22     {
  23         serie = s[[I(i)]] + rnorm(L,sd=0.01)
  24         level = mean(serie)
  25         serie = serie - level
  26         # 10 series with NAs for index 2
  27         if (I(i) == 2 && i >= 60 && i<= 90)
  28             serie[sample(seq_len(L),1)] = NA
  29         time = as.POSIXct(i*15*60, origin="2007-01-01", tz="GMT")
  30         exo = runif(4)
  31         exo_hat = runif(4)
  32         data$append(time, serie, level, exo, exo_hat)
  33     }
  34     data
  35 }
  36
  37 test_that("output is as expected on simulated series",
  38 {
  39     data = getDataTest(150)
  40
  41     # index 143 : serie type 2
  42     pred = computeForecast(data, 143, "Neighbors", "Zero",
  43         horizon=length(data$getSerie(1)), simtype="endo", h_window=1)
  44     f = computeFilaments(data, pred, 1, limit=60, plot=FALSE)
  45
  46     # Expected output: 50-3-10 series of type 2, then 23 series of type 3 (closest next)
  47     expect_identical(length(f$neighb_indices), as.integer(60))
  48     expect_identical(length(f$colors), as.integer(60))
  49     expect_equal(f$index, 143)
  50     expect_true(all(I(f$neighb_indices) >= 2))
  51     for (i in 1:37)
  52     {
  53         expect_equal(I(f$neighb_indices[i]), 2)
  54         expect_match(f$colors[i], f$colors[1])
  55     }
  56     for (i in 38:60)
  57     {
  58         expect_equal(I(f$neighb_indices[i]), 3)
  59         expect_match(f$colors[i], f$colors[38])
  60     }
  61     expect_match(f$colors[1], "#1*")
  62     expect_match(f$colors[38], "#E*")
  63
  64     # index 142 : serie type 1
  65     pred = computeForecast(data, 142, "Neighbors", "Zero",
  66         horizon=length(data$getSerie(1)), simtype="endo", h_window=1)
  67     f = computeFilaments(data, pred, 1, limit=50, plot=FALSE)
  68
  69     # Expected output: 50-10-3 series of type 1, then 13 series of type 3 (closest next)
  70     # NOTE: -10 because only past days with no-NAs tomorrow => exclude type 1 in [60,90[
  71     expect_identical(length(f$neighb_indices), as.integer(50))
  72     expect_identical(length(f$colors), as.integer(50))
  73     expect_equal(f$index, 142)
  74     expect_true(all(I(f$neighb_indices) != 2))
  75     for (i in 1:37)
  76     {
  77         expect_equal(I(f$neighb_indices[i]), 1)
  78         expect_match(f$colors[i], f$colors[1])
  79     }
  80     for (i in 38:50)
  81     {
  82         expect_equal(I(f$neighb_indices[i]), 3)
  83         expect_match(f$colors[i], f$colors[38])
  84     }
  85     expect_match(f$colors[1], "#1*")
  86     expect_match(f$colors[38], "#E*")
  87 })