adapt Bruno method into package, add 'operational' mode

[talweg.git] / pkg / tests / testthat / test-computeFilaments.R

diff --git a/pkg/tests/testthat/test-computeFilaments.R b/pkg/tests/testthat/test-computeFilaments.R
index 6169a77..0c58c69 100644 (file)
--- a/pkg/tests/testthat/test-computeFilaments.R
+++ b/pkg/tests/testthat/test-computeFilaments.R
@@ -4,55 +4,51 @@ test_that("output is as expected on simulated series",
 {
        data = getDataTest(150)
 
-
-
-
-#TODO: debug
-
-
-
-       # index 144-1 == 143 : serie type 2
-       pred = computeForecast(data, 143, "Neighbors", "Zero", predict_from=8,
-               horizon=length(data$getSerie(1)), simtype="endo", local=FALSE, h_window=1)
+       # index 144 : serie type 3, yersteday type 2
+       pred = computeForecast(data, 144, "Neighbors", "Zero", predict_from=1,
+               horizon=length(data$getSerie(1)), simtype="endo", local=FALSE, window=1, opera=TRUE)
        f = computeFilaments(data, pred, 1, 8, limit=60, plot=FALSE)
 
-       # Expected output: 50-3-10 series of type 2, then 23 series of type 3 (closest next)
+       # Expected output: 50-3-10 series of type 2+1 = 3,
+       # then 23 series of type 3+1 %% 3 = 1 (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))
+       expect_equal(f$index, 144)
+       expect_true(all(I(f$neighb_indices) != 2))
        for (i in 1:37)
        {
-               expect_equal(I(f$neighb_indices[i]), 2)
+               expect_equal(I(f$neighb_indices[i]), 3)
                expect_match(f$colors[i], f$colors[1])
        }
        for (i in 38:60)
        {
-               expect_equal(I(f$neighb_indices[i]), 3)
+               expect_equal(I(f$neighb_indices[i]), 1)
                expect_match(f$colors[i], f$colors[38])
        }
        expect_match(f$colors[1], "#1*")
        expect_match(f$colors[38], "#E*")
 
-       # index 143-1 == 142 : serie type 1
-       pred = computeForecast(data, 143, "Neighbors", "Zero", predict_from=8,
-               horizon=length(data$getSerie(1)), simtype="endo", local=FALSE, h_window=1)
+       # index 143 : serie type 2
+       pred = computeForecast(data, 143, "Neighbors", "Zero", predict_from=1,
+               horizon=length(data$getSerie(1)), simtype="endo", local=FALSE, window=1, opera=TRUE)
        f = computeFilaments(data, pred, 1, 8, limit=50, plot=FALSE)
 
-       # 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[
+       # Expected output: 50-10-3 series of type 1+1=2,
+       # then 13 series of type 3+1 %% 3 = 1 (closest next)
+       # NOTE: -10 because only past tomorrows with no-NAs yerstedays
+       #        => exclude type 2 in [60,90[
        expect_identical(length(f$neighb_indices), as.integer(50))
        expect_identical(length(f$colors), as.integer(50))
        expect_equal(f$index, 143)
-       expect_true(all(I(f$neighb_indices) != 2))
+       expect_true(all(I(f$neighb_indices) <= 2))
        for (i in 1:37)
        {
-               expect_equal(I(f$neighb_indices[i]), 1)
+               expect_equal(I(f$neighb_indices[i]), 2)
                expect_match(f$colors[i], f$colors[1])
        }
        for (i in 38:50)
        {
-               expect_equal(I(f$neighb_indices[i]), 3)
+               expect_equal(I(f$neighb_indices[i]), 1)
                expect_match(f$colors[i], f$colors[38])
        }
        expect_match(f$colors[1], "#1*")