diff --git a/tests/testthat/test-SeriesAggreg.R b/tests/testthat/test-SeriesAggreg.R
index f54edc9cf49a4d2ba1a2a326a210b3493d874610..cc6e0c2bc56fb4c1e7f38ba839ed352b00a56122 100644
--- a/tests/testthat/test-SeriesAggreg.R
+++ b/tests/testthat/test-SeriesAggreg.R
@@ -15,10 +15,11 @@ test_that("No warning with InputsModel Cemaneige'", {
NLayers = 5
)
# Expect no warning: https://stackoverflow.com/a/33638939/5300212
- expect_warning(SeriesAggreg(InputsModel, "%m"),
+ expect_warning(SeriesAggreg(InputsModel, Format = "%m"),
regexp = NA)
})
+
test_that("Warning: deprecated 'TimeFormat' argument", {
InputsModel <- CreateInputsModel(
FUN_MOD = RunModel_GR4J,
@@ -30,6 +31,7 @@ test_that("Warning: deprecated 'TimeFormat' argument", {
regexp = "deprecated 'TimeFormat' argument")
})
+
test_that("Warning: deprecated 'NewTimeFormat' argument: please use 'Format' instead",
{
InputsModel <- CreateInputsModel(
@@ -42,6 +44,7 @@ test_that("Warning: deprecated 'NewTimeFormat' argument: please use 'Format' ins
regexp = "deprecated 'NewTimeFormat' argument: please use 'Format' instead")
})
+
test_that("Warning: deprecated 'NewTimeFormat' argument: 'Format' argument is used instead",
{
InputsModel <- CreateInputsModel(
@@ -54,6 +57,7 @@ test_that("Warning: deprecated 'NewTimeFormat' argument: 'Format' argument is us
regexp = "deprecated 'NewTimeFormat' argument: 'Format' argument is used instead")
})
+
test_that("Check SeriesAggreg output values on yearly aggregation", {
TabSeries <- data.frame(
DatesR = BasinObs$DatesR,
@@ -72,6 +76,7 @@ test_that("Check SeriesAggreg output values on yearly aggregation", {
expect_equal(GoodValues, TestedValues)
})
+
test_that("Regime calculation should switch ConvertFun to 'mean' for InputsModel", {
InputsModel <- CreateInputsModel(
FUN_MOD = RunModel_GR4J,
@@ -79,11 +84,11 @@ test_that("Regime calculation should switch ConvertFun to 'mean' for InputsModel
Precip = BasinObs$P,
PotEvap = BasinObs$E
)
-
- expect_equal(SeriesAggreg(InputsModel, "%m")$Precip,
- SeriesAggreg(BasinObs[, c("DatesR", "P")], "%m", ConvertFun = "mean")$P)
+ expect_equal(SeriesAggreg(InputsModel, Format = "%m")$Precip,
+ SeriesAggreg(BasinObs[, c("DatesR", "P")], Format = "%m", ConvertFun = "mean")$P)
})
+
test_that("No DatesR should warning", {
TabSeries <- list(
Dates = BasinObs$DatesR,
@@ -92,11 +97,12 @@ test_that("No DatesR should warning", {
Qmm = BasinObs$Qmm
)
expect_warning(
- SeriesAggreg(TabSeries, "%Y%m", ConvertFun = "sum"),
+ SeriesAggreg(TabSeries, Format = "%Y%m", ConvertFun = "sum"),
regexp = "has been automatically chosen"
)
})
+
test_that("Check SeriesAggreg.list 'DatesR' argument", {
InputsModel <- CreateInputsModel(
FUN_MOD = RunModel_GR4J,
@@ -107,16 +113,17 @@ test_that("Check SeriesAggreg.list 'DatesR' argument", {
DatesR <- InputsModel$DatesR
# No InputsModel$DatesR
InputsModel$DatesR <- NULL
- expect_error(SeriesAggreg(InputsModel, "%Y%m"), regexp = "'POSIXt'")
+ expect_error(SeriesAggreg(InputsModel, Format = "%Y%m"), regexp = "'POSIXt'")
# Other list item chosen
InputsModel$SuperDates <- DatesR
- expect_warning(SeriesAggreg(InputsModel, "%Y%m"), regexp = "SuperDates")
+ expect_warning(SeriesAggreg(InputsModel, Format = "%Y%m"), regexp = "SuperDates")
# Wrong InputsModel$DatesR
InputsModel$DatesR <- BasinObs$P
- expect_error(SeriesAggreg(InputsModel, "%Y%m"), regexp = "'POSIXt'")
+ expect_error(SeriesAggreg(InputsModel, Format = "%Y%m"), regexp = "'POSIXt'")
})
+
test_that("Check SeriesAggreg.list with embedded lists", {
InputsModel <-
CreateInputsModel(
@@ -128,38 +135,36 @@ test_that("Check SeriesAggreg.list with embedded lists", {
HypsoData = BasinInfo$HypsoData,
NLayers = 5
)
- I2 <- SeriesAggreg(InputsModel, "%Y%m")
+ I2 <- SeriesAggreg(InputsModel, Format = "%Y%m")
expect_equal(length(I2$ZLayers), 5)
expect_null(I2$LayerPrecip$DatesR)
expect_equal(length(I2$DatesR), length(I2$LayerPrecip$L1))
})
+
test_that("Check SeriesAggreg.outputsModel", {
- InputsModel <-
- CreateInputsModel(
- FUN_MOD = RunModel_CemaNeigeGR4J,
- DatesR = BasinObs$DatesR,
- Precip = BasinObs$P,
- PotEvap = BasinObs$E,
- TempMean = BasinObs$T,
- ZInputs = median(BasinInfo$HypsoData),
- HypsoData = BasinInfo$HypsoData,
- NLayers = 5
- )
+ InputsModel <- CreateInputsModel(
+ FUN_MOD = RunModel_CemaNeigeGR4J,
+ DatesR = BasinObs$DatesR,
+ Precip = BasinObs$P,
+ PotEvap = BasinObs$E,
+ TempMean = BasinObs$T,
+ ZInputs = median(BasinInfo$HypsoData),
+ HypsoData = BasinInfo$HypsoData,
+ NLayers = 5
+ )
## run period selection
- Ind_Run <-
- seq(which(format(BasinObs$DatesR, format = "%Y-%m-%d") == "1990-01-01"),
- which(format(BasinObs$DatesR, format = "%Y-%m-%d") == "1999-12-31"))
+ Ind_Run <- seq(which(format(BasinObs$DatesR, format = "%Y-%m-%d") == "1990-01-01"),
+ which(format(BasinObs$DatesR, format = "%Y-%m-%d") == "1999-12-31"))
## preparation of the RunOptions object
suppressWarnings(
- RunOptions <-
- CreateRunOptions(
- FUN_MOD = RunModel_CemaNeigeGR4J,
- InputsModel = InputsModel,
- IndPeriod_Run = Ind_Run
- )
+ RunOptions <- CreateRunOptions(
+ FUN_MOD = RunModel_CemaNeigeGR4J,
+ InputsModel = InputsModel,
+ IndPeriod_Run = Ind_Run
+ )
)
## simulation
@@ -175,12 +180,13 @@ test_that("Check SeriesAggreg.outputsModel", {
RunOptions = RunOptions,
Param = Param)
- O2 <- SeriesAggreg(OutputsModel, "%Y%m")
+ O2 <- SeriesAggreg(OutputsModel, Format = "%Y%m")
expect_equal(length(O2$StateEnd), 3)
expect_equal(length(O2$DatesR),
length(O2$CemaNeigeLayers$Layer01$Pliq))
})
+
test_that("Check data.frame handling in SeriesAggreg.list", {
InputsModelDown1 <- CreateInputsModel(
FUN_MOD = RunModel_GR4J,
@@ -193,15 +199,16 @@ test_that("Check data.frame handling in SeriesAggreg.list", {
# Distance between upstream catchment outlet and the downstream one in km
BasinAreas = c(180, 180) # Upstream and downstream areas in km²
)
- expect_warning(SeriesAggreg(InputsModelDown1, "%Y%m"),
+ expect_warning(SeriesAggreg(InputsModelDown1, Format = "%Y%m"),
regexp = NA)
- I2 <- SeriesAggreg(InputsModelDown1, "%Y%m")
+ I2 <- SeriesAggreg(InputsModelDown1, Format = "%Y%m")
expect_equal(length(I2$DatesR), nrow(I2$Qupstream))
InputsModelDown1$Qupstream <- InputsModelDown1$Qupstream[-1, , drop = FALSE]
- expect_warning(SeriesAggreg(InputsModelDown1, "%Y%m"),
+ expect_warning(SeriesAggreg(InputsModelDown1, Format = "%Y%m"),
regexp = "it will be ignored in the aggregation")
})
+
test_that("SeriesAggreg from and to the same time step should return initial time series", {
InputsModel <- CreateInputsModel(
FUN_MOD = RunModel_GR4J,
@@ -209,42 +216,45 @@ test_that("SeriesAggreg from and to the same time step should return initial tim
Precip = BasinObs$P,
PotEvap = BasinObs$E
)
- I2 <- SeriesAggreg(InputsModel, "%Y%m")
- expect_warning(SeriesAggreg(I2, "%Y%m"), regexp = "No time-step conversion was performed")
- expect_equal(I2, suppressWarnings(SeriesAggreg(I2, "%Y%m")))
+ I2 <- SeriesAggreg(InputsModel, Format = "%Y%m")
+ expect_warning(SeriesAggreg(I2, Format = "%Y%m"), regexp = "No time-step conversion was performed")
+ expect_equal(I2, suppressWarnings(SeriesAggreg(I2, Format = "%Y%m")))
})
-test_that("SeriesAggreg.data.frame with first column not named DatesR should work",
- {
+
+test_that("SeriesAggreg.data.frame with first column not named DatesR should work", {
expect_warning(SeriesAggreg(
data.frame(BasinObs$DatesR, BasinObs$Qmm),
Format = "%Y%m",
ConvertFun = "sum"
),
regexp = NA)
- })
+})
+
test_that("SeriesAggreg should work with ConvertFun 'min', 'max' and 'median'", {
Qls <- BasinObs[, c("DatesR", "Qls")]
- test_ConvertFunRegime <- function(x, ConvertFun, TimeFormat) {
- expect_equal(nrow(SeriesAggreg(x, TimeFormat, ConvertFun = ConvertFun)),
- length(unique(format(BasinObs$DatesR, "%Y"))))
+ test_ConvertFunRegime <- function(x, ConvertFun, Format) {
+ expect_equal(nrow(SeriesAggreg(x, Format, ConvertFun = ConvertFun)),
+ length(unique(format(BasinObs$DatesR, format = "%Y"))))
}
- lapply(c("max", "min", "median"), function(x) {test_ConvertFunRegime(Qls, x, "%Y")})
+ lapply(c("max", "min", "median"), function(x) {test_ConvertFunRegime(Qls, x, Format = "%Y")})
})
+
test_that("Error on convertFun Q without 0-100", {
Qls <- BasinObs[, c("DatesR", "Qls")]
- expect_error(SeriesAggreg(Qls, "%Y", "q101"))
- expect_error(SeriesAggreg(Qls, "%Y", "q-2"))
- expect_error(SeriesAggreg(Qls, "%Y", "q12.5"))
+ expect_error(SeriesAggreg(Qls, Format = "%Y", "q101"))
+ expect_error(SeriesAggreg(Qls, Format = "%Y", "q-2"))
+ expect_error(SeriesAggreg(Qls, Format = "%Y", "q12.5"))
})
+
test_that("ConvertFun q50 should be equal to median", {
Qls <- BasinObs[, c("DatesR", "Qls")]
- expect_equal(SeriesAggreg(Qls, "%Y", "q50"),
- SeriesAggreg(Qls, "%Y", "median"))
- expect_equal(SeriesAggreg(Qls, "%Y", "q50"),
- SeriesAggreg(Qls, "%Y", "q050"))
+ expect_equal(SeriesAggreg(Qls, Format = "%Y", "q50"),
+ SeriesAggreg(Qls, Format = "%Y", "median"))
+ expect_equal(SeriesAggreg(Qls, Format = "%Y", "q50"),
+ SeriesAggreg(Qls, Format = "%Y", "q050"))
})