context("Check that computeFilaments behaves as expected")
-test_that("output is as expected on simulated series",
+#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)
{
- x = seq(0,10,0.1)
- L = length(x)
+ data = Data$new()
+ x = seq(0,9.5,0.1)
+ L = length(x) #96 1/4h
s1 = cos(x)
s2 = sin(x)
s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] )
- #sum((s1-s2)^2) == 97.59381
- #sum((s1-s3)^2) == 57.03051
- #sum((s2-s3)^2) == 40.5633
- s = list( s1, s2, s3 )
- n = 150
+ #sum((s1-s2)^2) == 96
+ #sum((s1-s3)^2) == 58
+ #sum((s2-s3)^2) == 38
+ s = list(s1, s2, s3)
series = list()
for (i in seq_len(n))
{
- index = (i%%3) + 1
- level = mean(s[[index]])
- serie = s[[index]] - level + rnorm(L,sd=0.05)
+ serie = s[[I(i)]] + rnorm(L,sd=0.01)
+ level = mean(serie)
+ serie = serie - level
# 10 series with NAs for index 2
- if (index == 2 && i >= 60 && i<= 90)
+ if (I(i) == 2 && i >= 60 && i<= 90)
serie[sample(seq_len(L),1)] = NA
- series[[i]] = list("level"=level,"serie"=serie) #no need for more
+ time = as.POSIXct(i*15*60, origin="2007-01-01", tz="GMT")
+ exo = runif(4)
+ exo_hat = runif(4)
+ data$append(time, serie, level, exo, exo_hat)
+ }
+ data
+}
+
+test_that("output is as expected on simulated series",
+{
+ data = getDataTest(150)
+
+ # index 143 : serie type 2
+ pred = computeForecast(data, 143, "Neighbors", "Zero",
+ horizon=length(data$getSerie(1)), simtype="endo", h_window=1)
+ f = computeFilaments(data, pred, 1, limit=60, plot=FALSE)
+
+ # Expected output: 50-3-10 series of type 2, then 23 series of type 3 (closest next)
+ expect_identical(length(f$neighb_indices), as.integer(60))
+ expect_identical(length(f$colors), as.integer(60))
+ expect_equal(f$index, 143)
+ expect_true(all(I(f$neighb_indices) >= 2))
+ for (i in 1:37)
+ {
+ expect_equal(I(f$neighb_indices[i]), 2)
+ expect_match(f$colors[i], f$colors[1])
+ }
+ for (i in 38:60)
+ {
+ expect_equal(I(f$neighb_indices[i]), 3)
+ expect_match(f$colors[i], f$colors[38])
}
- data = new("Data", data=series)
+ expect_match(f$colors[1], "#1*")
+ expect_match(f$colors[38], "#E*")
+
+ # index 142 : serie type 1
+ pred = computeForecast(data, 142, "Neighbors", "Zero",
+ horizon=length(data$getSerie(1)), simtype="endo", h_window=1)
+ f = computeFilaments(data, pred, 1, limit=50, plot=FALSE)
- # index 142 : serie type 2
- f2 = computeFilaments(data, 142, limit=60, plot=FALSE)
- # Expected output: 22 series of type 3 (closer), then 50-2-10 series of type 2
- #
- #
- #
- #
- #
- #
- # 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)])
- # index 143 : serie type 3
- f3 = computeFilaments(data, 143, limit=70, plot=FALSE)
- # Expected output: 22 series of type 2 (closer) then 50-2 series of type 3
- # ATTENTION au shift
- #
- #
- # index 144 : serie type 1
- f1 = computeFilaments(data, 144, limit=50, plot=FALSE)
- # Expected output: 2 series of type 3 (closer), then 50-2 series of type 1
- #
- expect_that( diff_norm, is_less_than(0.5) )
+ # 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$neighb_indices), as.integer(50))
+ expect_identical(length(f$colors), as.integer(50))
+ expect_equal(f$index, 142)
+ expect_true(all(I(f$neighb_indices) != 2))
+ for (i in 1:37)
+ {
+ expect_equal(I(f$neighb_indices[i]), 1)
+ expect_match(f$colors[i], f$colors[1])
+ }
+ for (i in 38:50)
+ {
+ expect_equal(I(f$neighb_indices[i]), 3)
+ expect_match(f$colors[i], f$colors[38])
+ }
+ expect_match(f$colors[1], "#1*")
+ expect_match(f$colors[38], "#E*")
})
projects / talweg.git / blobdiff