pkg/tests/testthat/test.Forecaster.R

   1 context("Check that forecasters behave as expected")
   2
   3 ts_data = system.file("testdata","ts_test.csv",package="talweg")
   4 exo_data = system.file("testdata","exo_test.csv",package="talweg")
   5 data00 <<- getData(ts_data, exo_data, input_tz="GMT", date_format="%Y-%m-%d %H:%M",
   6     working_tz="GMT", predict_at=0, limit=Inf)
   7 data13 <<- getData(ts_data, exo_data, input_tz="GMT", date_format="%Y-%m-%d %H:%M",
   8     working_tz="GMT", predict_at=13, limit=Inf)
   9 #Forecast at sunday to saturday (series 7 to 1), for monday to sunday (series 1 to 7)
  10 indices <<- seq(as.Date("2007-04-01"),as.Date("2007-04-07"),"days")
  11 pred_order = c(7,1:6) #will facilitate tests
  12
  13 test_that("Average method behave as expected",
  14 {
  15     pred00_z = computeForecast(data00, indices, "Average", "Zero",        Inf, 24)
  16     pred00_p = computeForecast(data00, indices, "Average", "Persistence", Inf, 24)
  17     for (i in 1:7)
  18     {
  19         #zero jump: should predict true values minus 1
  20         expect_equal( pred00_z$getSerie(i), rep(pred_order[i],24) )
  21         #persistence jump == 1: should predict true values
  22         expect_equal( pred00_p$getSerie(i), rep(i,24) )
  23     }
  24
  25     #NOTE: days become
  26     #1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 (14h-->0h then 1h-->13h)
  27     #No jump between days, thus zero and persistence are equivalent (and correct)
  28     pred13_z = computeForecast(data13, indices, "Average", "Zero",        Inf, 24)
  29     pred13_p = computeForecast(data13, indices, "Average", "Persistence", Inf, 24)
  30     for (i in 1:7)
  31     {
  32         expect_equal( pred13_z$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
  33         expect_equal( pred13_p$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
  34     }
  35
  36     #A few extra checks
  37     expect_equal( pred00_p$getIndexInData(2), dateIndexToInteger("2007-04-02",data00) )
  38     expect_equal( pred00_z$getIndexInData(2), dateIndexToInteger("2007-04-02",data00) )
  39     expect_equal( pred13_p$getIndexInData(5), dateIndexToInteger("2007-04-05",data13) )
  40     expect_equal( pred13_z$getIndexInData(5), dateIndexToInteger("2007-04-05",data13) )
  41 })
  42
  43 test_that("Persistence method behave as expected",
  44 {
  45     #Situation A: +Zero; (generally) correct if jump, wrong otherwise
  46     pred00_sd = computeForecast(data00, indices, "Persistence", "Zero", Inf, 24, same_day=TRUE)
  47     pred00_dd = computeForecast(data00, indices, "Persistence", "Zero", Inf, 24, same_day=FALSE)
  48     for (i in 1:7)
  49     {
  50         expect_equal(pred00_sd$getSerie(i), rep(pred_order[i],24))
  51         expect_equal(pred00_dd$getSerie(i), rep(pred_order[i],24))
  52     }
  53
  54     pred13_sd = computeForecast(data13, indices, "Persistence", "Zero", Inf, 24, same_day=TRUE)
  55     pred13_dd = computeForecast(data13, indices, "Persistence", "Zero", Inf, 24, same_day=FALSE)
  56     for (i in 2:6)
  57     {
  58         expect_equal(pred13_sd$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
  59         expect_equal(pred13_dd$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
  60     }
  61     #boundaries are special cases: OK if same day, quite wrong otherwise
  62     expect_equal(pred13_sd$getSerie(1), c( rep(1,11), rep(2,13) ) )
  63     expect_equal(pred13_dd$getSerie(1), c( rep(1,11), rep(-5,13) ) )
  64     expect_equal(pred13_sd$getSerie(7), c( rep(7,11), rep(1,13) ) )
  65     expect_equal(pred13_dd$getSerie(7), c( rep(7,11), rep(8,13) ) )
  66
  67     #Situation B: +Persistence, (generally) correct
  68     pred00_sd = computeForecast(data00, indices, "Persistence", "Persistence", Inf, 24, same_day=TRUE)
  69     pred00_dd = computeForecast(data00, indices, "Persistence", "Persistence", Inf, 24, same_day=FALSE)
  70     for (i in 3:7)
  71     {
  72         expect_equal(pred00_sd$getSerie(i), rep(i,24))
  73         expect_equal(pred00_dd$getSerie(i), rep(i,24))
  74     }
  75     #boundaries are special cases: OK if same day, quite wrong otherwise
  76     expect_equal(pred00_sd$getSerie(1), rep(1,24) )
  77     expect_equal(pred00_dd$getSerie(1), rep(8,24) )
  78     expect_equal(pred00_sd$getSerie(2), rep(2,24) )
  79     expect_equal(pred00_dd$getSerie(2), rep(-5,24) )
  80
  81     pred13_sd = computeForecast(data13, indices, "Persistence", "Persistence", Inf, 24, same_day=TRUE)
  82     pred13_dd = computeForecast(data13, indices, "Persistence", "Persistence", Inf, 24, same_day=FALSE)
  83     for (i in 2:6)
  84     {
  85         expect_equal(pred13_sd$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
  86         expect_equal(pred13_dd$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
  87     }
  88     #boundaries are special cases: OK if same day, quite wrong otherwise
  89     expect_equal(pred13_sd$getSerie(1), c( rep(1,11), rep(2,13) ) )
  90     expect_equal(pred13_dd$getSerie(1), c( rep(1,11), rep(-5,13) ) )
  91     expect_equal(pred13_sd$getSerie(7), c( rep(7,11), rep(1,13) ) )
  92     expect_equal(pred13_dd$getSerie(7), c( rep(7,11), rep(8,13) ) )
  93
  94     #A few extra checks
  95     expect_equal( pred00_sd$getIndexInData(3), dateIndexToInteger("2007-04-03",data00) )
  96     expect_equal( pred00_dd$getIndexInData(6), dateIndexToInteger("2007-04-06",data00) )
  97     expect_equal( pred13_sd$getIndexInData(3), dateIndexToInteger("2007-04-03",data13) )
  98     expect_equal( pred13_dd$getIndexInData(6), dateIndexToInteger("2007-04-06",data13) )
  99 })
 100
 101 test_that("Neighbors method behave as expected",
 102 {
 103     #Situation A: +Zero; correct if jump, wrong otherwise
 104     pred00 = computeForecast(data00, indices, "Neighbors", "Zero", Inf, 24, simtype="mix")
 105     for (i in 1:7)
 106         expect_equal(pred00$getSerie(i), rep(pred_order[i],24))
 107
 108     pred13 = computeForecast(data13, indices, "Persistence", "Zero", Inf, 24, simtype="mix")
 109     for (i in 1:7)
 110         expect_equal(pred13$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
 111
 112     #Situation B: +Neighbors, always predict bad (small, averaged) jump
 113     pred00 = computeForecast(data00, indices, "Neighbors", "Neighbors", Inf, 24, simtype="endo")
 114     #Concerning weights, there are 12+(1 if i>=2) gaps at -6 and 90-12+(i-2 if i>=3) gaps at 1
 115     #Thus, predicted jump is respectively
 116     #  (12*-6+78)/90 = 0.06666667
 117     #  (13*-6+78)/91 = 0
 118     #  (13*-6+79)/92 = 0.01086957
 119     #  (13*-6+80)/93 = 0.02150538
 120     #  (13*-6+81)/94 = 0.03191489
 121     #  (13*-6+82)/95 = 0.04210526
 122     #  (13*-6+83)/96 = 0.05208333
 123     jumps = c(0.06666667, 0, 0.01086957, 0.02150538, 0.03191489, 0.04210526, 0.05208333)
 124     for (i in 1:7)
 125         expect_equal(pred00$getSerie(i), rep(pred_order[i]+jumps[i],24))
 126
 127     #Next lines commented out because too unpredictable results (tendency to flatten everything...)
 128 #   pred13 = computeForecast(data13, indices, "Neighbors", "Neighbors", Inf, 24, simtype="endo")
 129 #   for (i in 1:7)
 130 #       expect_equal(pred13$getSerie(i), c( rep(i,11), rep(i%%7+1,13) ) )
 131
 132     #A few extra checks
 133     expect_equal( pred00$getIndexInData(1), dateIndexToInteger("2007-04-01",data00) )
 134     expect_equal( pred00$getIndexInData(4), dateIndexToInteger("2007-04-04",data00) )
 135     expect_equal( pred13$getIndexInData(1), dateIndexToInteger("2007-04-01",data13) )
 136     expect_equal( pred13$getIndexInData(4), dateIndexToInteger("2007-04-04",data13) )
 137 })