X-Git-Url: https://git.auder.net/?a=blobdiff_plain;f=pkg%2Ftests%2Ftestthat%2Ftest.computeFilaments.R;h=ec39340af424847e263d91108eeb591c9d32e779;hb=8f84543c2d469933d0fc122543d3eeb824970011;hp=e8f87521e13d14dcb3108e6197b99dfe8a040dd2;hpb=6d97bfecf7310ed6682eecce1b7aa2f8185d4742;p=talweg.git diff --git a/pkg/tests/testthat/test.computeFilaments.R b/pkg/tests/testthat/test.computeFilaments.R index e8f8752..ec39340 100644 --- a/pkg/tests/testthat/test.computeFilaments.R +++ b/pkg/tests/testthat/test.computeFilaments.R @@ -1,103 +1,87 @@ context("Check that computeFilaments behaves as expected") -getDataTest = function(n, shift) +#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$new() + x = seq(0,9.5,0.1) + L = length(x) #96 1/4h s1 = cos(x) s2 = sin(x) s3 = c( s1[1:(L%/%2)] , s2[(L%/%2+1):L] ) - #sum((s1-s2)^2) == 97.59381 - #sum((s1-s3)^2) == 57.03051 - #sum((s2-s3)^2) == 40.5633 - s = list( s1, s2, s3 ) + #sum((s1-s2)^2) == 96 + #sum((s1-s3)^2) == 58 + #sum((s2-s3)^2) == 38 + s = list(s1, s2, s3) series = list() for (i in seq_len(n)) { - index = (i%%3) + 1 - level = mean(s[[index]]) - serie = s[[index]] - level + rnorm(L,sd=0.05) + serie = s[[I(i)]] + rnorm(L,sd=0.01) + level = mean(serie) + serie = serie - level # 10 series with NAs for index 2 - if (index == 2 && i >= 60 && i<= 90) + if (I(i) == 2 && i >= 60 && i<= 90) serie[sample(seq_len(L),1)] = NA - series[[i]] = list("level"=level,"serie"=serie) #no need for more - } - if (shift) - { - # Simulate shift at origin when predict_at > 0 - series[2:(n+1)] = series[1:n] - series[[1]] = list("level"=0, "serie"=s[[1]][1:(L%/%2)]) + time = as.POSIXct(i*15*60, origin="2007-01-01", tz="GMT") + exo = runif(4) + exo_hat = runif(4) + data$append(time, serie, level, exo, exo_hat) } - new("Data", data=series) + data } test_that("output is as expected on simulated series", { - data = getDataTest(150, FALSE) - - # index 142 : serie type 2 - f = computeFilaments(data, 142, limit=60, plot=FALSE) - # Expected output: 22 series of type 3 (closer), then 50-2-10 series of type 2 - expect_identical(length(f$indices), 60) - expect_identical(length(f$colors), 60) - for (i in 1:22) - { - expect_identical((f$indices[i] %% 3) + 1, 3) - expect_match(f2$colors[i], f$colors[1]) - } - for (i in 23:60) - { - expect_identical((f$indices[i] %% 3) + 1, 2) - expect_match(f2$colors[i], f$colors[23]) - } - expect_match(colors[1], "...") - expect_match(colors[23], "...") -}) + data = getDataTest(150) -test_that("output is as expected on simulated series", -{ - data = getDataTest(150, TRUE) + # index 143 : serie type 2 + pred = computeForecast(data, 143, "Neighbors", "Zero", + horizon=length(data$getSerie(1)), simtype="endo", h_window=1) + f = computeFilaments(data, pred, 1, limit=60, plot=FALSE) - # index 143 : serie type 3 - f = computeFilaments(data, 143, limit=70, plot=FALSE) - # Expected output: 22 series of type 2 (closer) then 50-2 series of type 3 - expect_identical(length(f$indices), 70) - expect_identical(length(f$colors), 70) - for (i in 1:22) + # Expected output: 50-3-10 series of type 2, then 23 series of type 3 (closest next) + expect_identical(length(f$neighb_indices), as.integer(60)) + expect_identical(length(f$colors), as.integer(60)) + expect_equal(f$index, 143) + expect_true(all(I(f$neighb_indices) >= 2)) + for (i in 1:37) { - # -1 because of the initial shift - expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 2) + expect_equal(I(f$neighb_indices[i]), 2) expect_match(f$colors[i], f$colors[1]) } - for (i in 23:70) + for (i in 38:60) { - expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 3) - expect_match(f$colors[i], f$colors[23]) + expect_equal(I(f$neighb_indices[i]), 3) + expect_match(f$colors[i], f$colors[38]) } - expect_match(colors[1], "...") - expect_match(colors[23], "...") -}) + expect_match(f$colors[1], "#1*") + expect_match(f$colors[38], "#E*") -test_that("output is as expected on simulated series", -{ - data = getDataTest(150, TRUE) + # index 142 : serie type 1 + pred = computeForecast(data, 142, "Neighbors", "Zero", + horizon=length(data$getSerie(1)), simtype="endo", h_window=1) + f = computeFilaments(data, pred, 1, limit=50, plot=FALSE) - # index 144 : serie type 1 - f = computeFilaments(data, 144, limit=50, plot=FALSE) - # Expected output: 2 series of type 3 (closer), then 50-2 series of type 1 - expect_identical(length(f$indices), 50) - expect_identical(length(f$colors), 50) - for (i in 1:2) + # 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) { - # -1 because of the initial shift - expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 3) + expect_equal(I(f$neighb_indices[i]), 1) expect_match(f$colors[i], f$colors[1]) } - for (i in 3:50) + for (i in 38:50) { - expect_identical(( (f$indices[i]-1) %% 3 ) + 1, 1) - expect_match(f$colors[i], f$colors[3]) + expect_equal(I(f$neighb_indices[i]), 3) + expect_match(f$colors[i], f$colors[38]) } - expect_match(colors[1], "...") - expect_match(colors[3], "...") + expect_match(f$colors[1], "#1*") + expect_match(f$colors[38], "#E*") })