X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2Ftests%2Ftestthat%2Ftest.computeFilaments.R;h=ec39340af424847e263d91108eeb591c9d32e779;hb=102bcfda4afbb5cfee885cbee0f55545624168fd;hp=46f2e3f94a2431eef7c797567d898cc6e455441e;hpb=a65907cc939a5fe419613d3ba555b1d1c1af97d3;p=talweg.git

diff --git a/pkg/tests/testthat/test.computeFilaments.R b/pkg/tests/testthat/test.computeFilaments.R
index 46f2e3f..ec39340 100644
--- a/pkg/tests/testthat/test.computeFilaments.R
+++ b/pkg/tests/testthat/test.computeFilaments.R
@@ -1,51 +1,87 @@
 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*")
 })