Nothing
context("comb_EIG2")
test_that("Forward wrong input to EIG2", {
expect_error(comb_EIG2(1))
expect_error(comb_EIG2("abs"))
expect_error(comb_EIG2(list(a=1, b=2)))
expect_error(comb_EIG2(NULL))
expect_error(comb_EIG2(NA))
expect_error(comb_EIG2(Inf))
expect_error(comb_EIG2(-Inf))
})
test_that("Check for correct class type and accuracy, when only train set is used", {
set.seed(5)
obs <- rnorm(100)
preds <- matrix(rnorm(1000, 1), 100, 10)
train_o<-obs[1:80]
train_p<-preds[1:80,]
data<-foreccomb(train_o, train_p)
result<-comb_EIG2(data)
expect_is(result, "foreccomb_res")
expect_length(result, 8)
expect_equal(as.vector(result$Accuracy_Train),
c(2.196045e-16, 1.033257, 0.8223281, 97.7288, 146.469, 0.1243176, 1.017865),
tolerance = 1e-5,
check.attributes = FALSE)
})
test_that( "Check for correct class type and accuracy, when Forecast_Test is provided but not Actual_Test", {
set.seed(5)
obs <- rnorm(100)
preds <- matrix(rnorm(1000, 1), 100, 10)
train_o<-obs[1:80]
train_p<-preds[1:80,]
test_p<-preds[81:100,]
data<-foreccomb(train_o, train_p, newpreds = test_p)
result<-comb_EIG2(data)
expect_is(result, "foreccomb_res")
expect_length(result, 9)
expect_equal(as.vector(result$Accuracy_Train),
c(2.196045e-16, 1.033257, 0.8223281, 97.7288, 146.469, 0.1243176, 1.017865),
tolerance = 1e-5,
check.attributes = FALSE)
})
test_that( "Check for correct class type and accuracy, when test set is used", {
set.seed(5)
obs <- rnorm(100)
preds <- matrix(rnorm(1000, 1), 100, 10)
train_o<-obs[1:80]
train_p<-preds[1:80,]
test_o<-obs[81:100]
test_p<-preds[81:100,]
data<-foreccomb(train_o, train_p, test_o, test_p)
result<-comb_EIG2(data)
expect_is(result, "foreccomb_res")
expect_length(result, 10)
expect_equal(as.vector(result$Accuracy_Test),
c(0.07977107, 1.00866943, 0.83392937, 232.27308969, 240.32910851),
tolerance = 1e-5,
check.attributes = FALSE)
})
test_that( "Check for correct combination, when test set is used with the predict function (simplified)", {
set.seed(5)
obs <- rnorm(100)
preds <- matrix(rnorm(1000, 1), 100, 10)
train_o<-obs[1:80]
train_p<-preds[1:80,]
test_p<-preds[81:100,]
data<-foreccomb(train_o, train_p)
result<-comb_EIG2(data)
data2<-foreccomb(train_o, train_p, newpreds=test_p)
result2<-comb_EIG2(data2)
preds <- predict(result, test_p, simplify = TRUE)
expect_equal(as.vector(preds)[1:5],
result2$Forecasts_Test[1:5],
tolerance = 1e-5,
check.attributes = FALSE)
})
test_that( "Check for correct combination, when test set is used with the predict function (extend object)", {
set.seed(5)
obs <- rnorm(100)
preds <- matrix(rnorm(1000, 1), 100, 10)
train_o<-obs[1:80]
train_p<-preds[1:80,]
test_p<-preds[81:100,]
data<-foreccomb(train_o, train_p)
result<-comb_EIG2(data)
data2<-foreccomb(train_o, train_p, newpreds=test_p)
result2<-comb_EIG2(data2)
preds <- predict(result, test_p, simplify = FALSE)
expect_equal(as.vector(preds$Forecasts_Test)[1:5],
result2$Forecasts_Test[1:5],
tolerance = 1e-5,
check.attributes = FALSE)
})
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