style(test): indent code and add missing argument names in the test-SeriesAggreg.R file

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"))
 })