context("Check that computeFilaments behaves as expected")
+#shorthand: map 1->1, 2->2, 3->3, 4->1, ..., 149->2, 150->3
+I = function(i)
+ (i-1) %% 3 + 1
+
#MOCK data; NOTE: could be in inst/testdata as well
-getDataTest = function(n, shift)
+getDataTest = function(n)
{
- x = seq(0,10,0.1)
- L = length(x)
+ data = Data$new()
+ x = seq(0,9.5,0.1)
+ L = length(x) #96 1/4h
s1 = cos(x)
s2 = sin(x)
s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] )
- #sum((s1-s2)^2) == 97.59381
- #sum((s1-s3)^2) == 57.03051
- #sum((s2-s3)^2) == 40.5633
- s = list( s1, s2, s3 )
+ #sum((s1-s2)^2) == 96
+ #sum((s1-s3)^2) == 58
+ #sum((s2-s3)^2) == 38
+ s = list(s1, s2, s3)
series = list()
for (i in seq_len(n))
{
- index = (i-1) %% 3 + 1 #map 1->1, 2->2, 3->3, 4->1, ..., 149->2, 150->3
- level = mean(s[[index]])
- serie = s[[index]] - level + rnorm(L,sd=0.01)
+ serie = s[[I(i)]] + rnorm(L,sd=0.01)
+ level = mean(serie)
+ serie = serie - level
# 10 series with NAs for index 2
- if (index == 2 && i >= 60 && i<= 90)
+ if (I(i) == 2 && i >= 60 && i<= 90)
serie[sample(seq_len(L),1)] = NA
- series[[i]] = list("level"=level,"serie"=serie) #no need for more
- }
- if (shift)
- {
- # Simulate shift at origin when predict_at > 0
- series[2:(n+1)] = series[1:n]
- series[[1]] = list("level"=0, "serie"=s[[1]][1:(L%/%2)])
+ time = as.POSIXct(i*15*60, origin="2007-01-01", tz="GMT")
+ exo = runif(4)
+ exo_hat = runif(4)
+ data$append(time, serie, level, exo, exo_hat)
}
- new("Data", data=series)
+ data
}
-test_that("output is as expected on simulated series, predict_at == 0",
+test_that("output is as expected on simulated series",
{
- data = getDataTest(150, shift=FALSE)
+ data = getDataTest(150)
# index 143 : serie type 2
- f = computeFilaments(data, 143, limit=60, plot=FALSE)
- # Expected output: 23 series of type 3 (closer), then 50-3-10 series of type 2, then index 143
- expect_identical(length(f$indices), as.integer(61)) #61 because result also contain "today"
- expect_identical(length(f$colors), as.integer(61))
- for (i in 1:23)
- {
- expect_equal((f$indices[i]-1) %% 3 + 1, 3)
- expect_match(f$colors[i], f$colors[1])
- }
- for (i in 24:60)
- {
- expect_equal((f$indices[i]-1) %% 3 + 1, 2)
- expect_match(f$colors[i], f$colors[24])
- }
- expect_equal(f$indices[61], 143)
- expect_match(f$colors[61], "#FF0000") #special color: current day in red
- expect_match(f$colors[1], "#E*")
- expect_match(f$colors[24], "#1*")
-})
-
-test_that("output is as expected on simulated series, predict_at > 0",
-{
- data = getDataTest(150, shift=TRUE)
+ pred = computeForecast(data, 143, "Neighbors", "Zero",
+ horizon=length(data$getSerie(1)), simtype="endo", h_window=1)
+ f = computeFilaments(data, pred, 1, limit=60, plot=FALSE)
- # index 142 : serie type 3
- f = computeFilaments(data, 142, limit=70, plot=FALSE)
- # Expected output: 24 series of type 2 (closer) then 50-4 series of type 3, then 142
- expect_identical(length(f$indices), as.integer(71))
- expect_identical(length(f$colors), as.integer(71))
- expect_true(all(f$indices >= 2)) #no type-1 neighbors
- for (i in 1:24)
+ # Expected output: 50-3-10 series of type 2, then 23 series of type 3 (closest next)
+ expect_identical(length(f$neighb_indices), as.integer(60))
+ expect_identical(length(f$colors), as.integer(60))
+ expect_equal(f$index, 143)
+ expect_true(all(I(f$neighb_indices) >= 2))
+ for (i in 1:37)
{
- # -1 + -1 because of the initial shift
- expect_equal((f$indices[i]-2) %% 3 + 1, 2)
+ expect_equal(I(f$neighb_indices[i]), 2)
expect_match(f$colors[i], f$colors[1])
}
- for (i in 25:70)
+ for (i in 38:60)
{
- expect_equal((f$indices[i]-2) %% 3 + 1, 3)
- expect_match(f$colors[i], f$colors[25])
+ expect_equal(I(f$neighb_indices[i]), 3)
+ expect_match(f$colors[i], f$colors[38])
}
- expect_equal(f$indices[71], 142)
- expect_match(f$colors[71], "#FF0000")
- expect_match(f$colors[1], "#E*")
- expect_match(f$colors[25], "#1*")
-})
+ expect_match(f$colors[1], "#1*")
+ expect_match(f$colors[38], "#E*")
-test_that("output is as expected on simulated series",
-{
- data = getDataTest(150, shift=TRUE)
+ # index 142 : serie type 1
+ pred = computeForecast(data, 142, "Neighbors", "Zero",
+ horizon=length(data$getSerie(1)), simtype="endo", h_window=1)
+ f = computeFilaments(data, pred, 1, limit=50, plot=FALSE)
- # index 143 : serie type 1
- f = computeFilaments(data, 143, limit=60, plot=FALSE)
- # Expected output: 23 series of type 3 (closer), then 50-10-3 series of type 1, then 143
+ # Expected output: 50-10-3 series of type 1, then 13 series of type 3 (closest next)
# NOTE: -10 because only past days with no-NAs tomorrow => exclude type 1 in [60,90[
- expect_identical(length(f$indices), as.integer(61))
- expect_identical(length(f$colors), as.integer(61))
- expect_true(all(f$indices >= 2)) #first_day should be 2
- for (i in 1:23)
+ expect_identical(length(f$neighb_indices), as.integer(50))
+ expect_identical(length(f$colors), as.integer(50))
+ expect_equal(f$index, 142)
+ expect_true(all(I(f$neighb_indices) != 2))
+ for (i in 1:37)
{
- expect_equal(( (f$indices[i]-2) %% 3 ) + 1, 3)
+ expect_equal(I(f$neighb_indices[i]), 1)
expect_match(f$colors[i], f$colors[1])
}
- for (i in 24:60)
+ for (i in 38:50)
{
- expect_equal(( (f$indices[i]-2) %% 3 ) + 1, 1)
- expect_match(f$colors[i], f$colors[24])
+ expect_equal(I(f$neighb_indices[i]), 3)
+ expect_match(f$colors[i], f$colors[38])
}
- expect_equal(f$indices[61], 143)
- expect_match(f$colors[61], "#FF0000")
- expect_match(f$colors[1], "#E*")
- expect_match(f$colors[24], "#1*")
+ expect_match(f$colors[1], "#1*")
+ expect_match(f$colors[38], "#E*")
})