From c02b4fa27913534d4f2cafc59fcc819bb2b9140c Mon Sep 17 00:00:00 2001
From: aho <an.ho@bsc.es>
Date: Thu, 30 Jan 2020 16:13:54 +0100
Subject: [PATCH 1/2] Season() + Apply. Unit test added.

---
 DESCRIPTION                  |   3 +-
 NAMESPACE                    |   1 +
 R/Season.R                   | 230 ++++++++++++++++++++++-------------
 man/Season.Rd                |  77 ++++++------
 tests/testthat/test-Season.R | 122 +++++++++++++++++++
 5 files changed, 307 insertions(+), 126 deletions(-)
 create mode 100644 tests/testthat/test-Season.R

diff --git a/DESCRIPTION b/DESCRIPTION
index 0045265c..6780c83d 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -50,7 +50,8 @@ Imports:
     ncdf4,
     parallel,
     plyr,
-    SpecsVerification (>= 0.5.0)
+    SpecsVerification (>= 0.5.0),
+    multiApply (>= 2.0.0)
 Suggests:
     easyVerification,
     testthat
diff --git a/NAMESPACE b/NAMESPACE
index 4e855789..00c59bfa 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -90,6 +90,7 @@ import(graphics)
 import(mapproj)
 import(maps)
 import(methods)
+import(multiApply)
 import(ncdf4)
 import(parallel)
 import(plyr)
diff --git a/R/Season.R b/R/Season.R
index baa19bbc..22b3578c 100644
--- a/R/Season.R
+++ b/R/Season.R
@@ -1,98 +1,154 @@
-#'Computes Seasonal Means
+#'Compute seasonal mean
 #'
-#'Computes seasonal means on timeseries organized in a array of any number of 
-#'dimensions up to 10 dimensions where the time dimension is one of those 10 
-#'dimensions.
+#'Compute the seasonal mean (or other methods) on monthly time series along
+#'one dimension of a named multi-dimensional arrays. Partial season is not 
+#'accounted.
 #'
-#'@param var Array containing the timeseries along one of its dimensions. 
-#'@param posdim Dimension along which to compute seasonal means = Time 
-#'  dimension.
-#'@param monini an integer indicating the first month of the time series: 1 to 
-#'  12.
-#'@param moninf an integer indicating the month when to start the seasonal 
-#'  means: 1 to 12.
-#'@param monsup an integer indicating the month when to stop the seasonal 
-#'  means: 1 to 12.
+#'@param data A named numeric array with at least one dimension 'time_dim'. 
+#'@param time_dim A character string indicating the name of dimension along  
+#'  which the seasonal means are computed. The default value is 'sdate'.
+#'@param monini An integer indicating what the first month of the time series is. 
+#'  It can be from 1 to 12.
+#'@param moninf An integer indicating the starting month of the seasonal mean. 
+#'  It can be from 1 to 12.
+#'@param monsup An integer indicating the end month of the seasonal mean. It 
+#'  can be from 1 to 12.
+#'@param method An R function to be applied for seasonal calculation. For
+#'  example, 'sum' can be used for total precipitation. The default value is mean.
+#'@param na.rm A logical value indicating whether to remove NA values along 
+#'  'time_dim' when calculating climatology (TRUE) or return NA if there is NA 
+#'  along 'time_dim' (FALSE). The default value is TRUE.
+#'@param ncores An integer indicating the number of cores to use for parallel 
+#'  computation. The default value is NULL.
 #'
-#'@return Array with the same dimensions as var except along the posdim 
-#'  dimension whose length corresponds to the number of seasons. Partial 
-#'  seasons are not accounted for.
-#'@keywords datagen
-#'@author History:\cr
-#'0.1  -  2011-03  (V. Guemas, \email{virginie.guemas@ic3.cat})  -  Original code\cr
-#'1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens@ic3.cat})  -  Formatting to CRAN
+#'@return An array with the same dimensions as data except along the 'time_dim' 
+#'  dimension, of which the length changes to the number of seasons.
+#'
+#'@import multiApply
 #'@examples
-#'# Load sample data as in Load() example:
-#'example(Load)
-#'leadtimes_dimension <- 4
-#'initial_month <- 11
-#'mean_start_month <- 12
-#'mean_stop_month <- 2
-#'season_means_mod <- Season(sampleData$mod, leadtimes_dimension, initial_month,
-#'                           mean_start_month, mean_stop_month)
-#'season_means_obs <- Season(sampleData$obs, leadtimes_dimension, initial_month,
-#'                           mean_start_month, mean_stop_month)
-#'  \donttest{
-#'PlotAno(season_means_mod, season_means_obs, startDates, 
-#'        toptitle = paste('winter (DJF) temperatures'), ytitle = c('K'), 
-#'        legends = 'ERSST', biglab = FALSE, fileout = 'tos_season_means.eps')
-#'  }
+#'dat <- 1 : (12 * 5 * 2 * 3 * 2)
+#'dim(dat) <- c(dat = 1, memb = 3, time = 12 * 5, lon = 2, lat = 2) 
+#'res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
+#'dat <- 1 : (12 * 2 * 3)
+#'dim(dat) <- c(dat = 2, time = 12, memb = 3)
+#'res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
+#'dat <- 1 : (24 * 2 * 3)
+#'dim(dat) <- c(dat = 2, time = 24, memb = 3)
+#'res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
+#'dat[c(1, 20, 50)] <- NA
+#'res1 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = FALSE)
+#'res2 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = TRUE)
+#'@import multiApply
 #'@export
-Season <- function(var, posdim = 4, monini, moninf, monsup) {
-  while (monsup < moninf) {
-    monsup <- monsup + 12
+Season <- function(data, time_dim = 'sdate', monini, moninf, monsup, 
+                   method = mean, na.rm = TRUE, ncores = NULL) {
+
+  # Check inputs 
+  ## data
+  if (is.null(data)) {
+    stop("Parameter 'data' cannot be NULL.")
   }
-  #
-  #  Enlarge the size of var to 10 
-  # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-  # 
-  dimsvar <- dim(var)
-  if (is.null(dimsvar)) {
-    dimsvar <- length(var)
+  if (!is.numeric(data)) {
+    stop("Parameter 'data' must be a numeric array.")
   }
-  ntime <- dimsvar[posdim]
-  enlvar <- Enlarge(var, 10)
-  outdim <- c(dimsvar, array(1, dim = (10 - length(dimsvar))))
-  u <- IniListDims(outdim, 10)
-  v <- IniListDims(outdim, 10)
-  #
-  #  Compute the seasonal means 
-  # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-  #
-  ind <- 1:ntime
-  months <- ((ind - 1) + monini - 1) %% 12 + 1
-  years <- ((ind - 1) + monini - 1) %/% 12
-
-  for (jmon in moninf:monsup) {
-    u[[posdim]] <- ind[which(months == ((jmon - 1) %% 12 + 1))]
-    ind0 <- u[[posdim]][1]
-    indf <- u[[posdim]][length(u[[posdim]])]
-    if (indf > (ntime - (monsup - jmon))) {
-      u[[posdim]] <- u[[posdim]][-which(u[[posdim]] == indf)]
+  if (is.null(dim(data))) {  #is vector
+    dim(data) <- c(length(data))
+    names(dim(data)) <- time_dim
+  }
+  if(any(is.null(names(dim(data))))| any(nchar(names(dim(data))) == 0)) {
+    stop("Parameter 'data' must have dimension names.")
+  }
+  ## time_dim
+  if (!is.character(time_dim) | length(time_dim) > 1) {
+    stop("Parameter 'time_dim' must be a character string.")
+  }
+  if (!time_dim %in% names(dim(data))) {
+    stop("Parameter 'time_dim' is not found in 'data' dimension.")
+  }
+  ## monini
+  if (!is.numeric(monini)) {
+    stop("Parameter 'monini' must be a positive integer between 1 and 12.")
+  } else {
+    if (monini %% 1 != 0 | monini < 1 | monini > 12 | length(monini) > 1) {
+      stop("Parameter 'monini' must be a positive integer between 1 and 12.")
     }
-    if (ind0 < (jmon - moninf + 1)) {
-      u[[posdim]] <- u[[posdim]][-which(u[[posdim]] == ind0)]
-    } 
-    if (jmon == moninf) { 
-      nseas <- length(u[[posdim]])
-      dimsvar[posdim] <- nseas
-      outdim[posdim] <- nseas
-      enlvarout <- array(0, dim = outdim)
+  }
+  ## moninf
+  if (!is.numeric(moninf)) {
+    stop("Parameter 'moninf' must be a positive integer between 1 and 12.")
+  } else {
+    if (moninf %% 1 != 0 | moninf < 1 | moninf > 12 | length(moninf) > 1) {
+      stop("Parameter 'moninf' must be a positive integer between 1 and 12.")
+    }
+  }
+  ## monsup
+  if (!is.numeric(monsup)) {
+    stop("Parameter 'monsup' must be a positive integer between 1 and 12.")
+  } else {
+    if (monsup %% 1 != 0 | monsup < 1 | monsup > 12 | length(monsup) > 1) {
+      stop("Parameter 'monsup' must be a positive integer between 1 and 12.")
     }
-    v[[posdim]] <- 1:nseas
-    enlvarout[v[[1]], v[[2]], v[[3]], v[[4]], v[[5]], v[[6]], v[[7]], v[[8]], 
-              v[[9]], v[[10]]] <- enlvarout[v[[1]], v[[2]], v[[3]], v[[4]],
-                                            v[[5]], v[[6]], v[[7]], v[[8]], 
-                                            v[[9]], v[[10]]] + enlvar[u[[1]], 
-                                  u[[2]], u[[3]], u[[4]], u[[5]], u[[6]], 
-                                  u[[7]], u[[8]], u[[9]], u[[10]]]
   }
-  varout <- array(dim = dimsvar)
-  varout[] <- enlvarout
-  varout <- varout / (monsup - moninf + 1)
-  #
-  #  Outputs
-  # ~~~~~~~~~
-  #
-  varout
+  ## method
+  if (!is.function(method)) {
+    stop("Parameter 'method' should be an existing R function, e.g., mean or sum.")
+  }
+  ## na.rm
+  if (!is.logical(na.rm) | length(na.rm) > 1) {
+    stop("Parameter 'na.rm' must be one logical value.")
+  }
+  ## ncores
+  if (!is.null(ncores)) {
+    if (!is.numeric(ncores) | ncores %% 1 != 0 | ncores < 0 |
+      length(ncores) > 1) {
+      stop("Parameter 'ncores' must be a positive integer.")
+    }
+  } 
+
+  ###############################
+  # Calculate Season
+
+    # Correction need if monini is not January: 
+    moninf <- moninf - monini + 1
+    monsup <- monsup - monini + 1
+    moninf <- ifelse(moninf <= 0, moninf + 12, moninf)
+    monsup <- ifelse(monsup <= 0, monsup + 12, monsup)
+
+    while (monsup < moninf) {
+        monsup <- monsup + 12
+    }
+
+    res <- Apply(list(data), 
+                 target_dims = time_dim, 
+                 output_dims = time_dim,
+                 fun = .Season, 
+                 monini = monini, moninf = moninf, monsup = monsup,
+                 method = method, na.rm = na.rm, ncores = ncores)$output1
+
+    return(res)
 }
+
+.Season <- function(x, monini, moninf, monsup, method = mean, na.rm = TRUE) {
+
+    #### Create position index:
+    # Basic index:
+    pos <- moninf : monsup
+    # Extended index for all period:
+    if (length(x) > pos[length(pos)]) {
+        pos2 <- lapply(pos, function(y) {seq(y, length(x), 12)})
+    } else {
+        pos2 <- pos
+    }
+    # Correct if the final season is not complete:
+    maxyear <- min(unlist(lapply(pos2, length)))
+    pos2 <- lapply(pos2, function(y) {y[1 : maxyear]})
+    # Convert to array:
+    pos2 <- unlist(pos2)
+    dim(pos2) <- c(year = maxyear, month = length(pos2)/maxyear)
+
+    timeseries <- apply(pos2, 1, function(y) {method(x[y], na.rm = na.rm)})
+    timeseries <- as.array(timeseries)
+
+    return(timeseries)
+}
+
diff --git a/man/Season.Rd b/man/Season.Rd
index cc97941c..f1e74d6a 100644
--- a/man/Season.Rd
+++ b/man/Season.Rd
@@ -2,56 +2,57 @@
 % Please edit documentation in R/Season.R
 \name{Season}
 \alias{Season}
-\title{Computes Seasonal Means}
+\title{Compute seasonal mean}
 \usage{
-Season(var, posdim = 4, monini, moninf, monsup)
+Season(data, time_dim = "sdate", monini, moninf, monsup, method = mean,
+  na.rm = TRUE, ncores = NULL)
 }
 \arguments{
-\item{var}{Array containing the timeseries along one of its dimensions.}
+\item{data}{A named numeric array with at least one dimension 'time_dim'.}
 
-\item{posdim}{Dimension along which to compute seasonal means = Time 
-dimension.}
+\item{time_dim}{A character string indicating the name of dimension along
+which the seasonal means are computed. The default value is 'sdate'.}
 
-\item{monini}{an integer indicating the first month of the time series: 1 to 
-12.}
+\item{monini}{An integer indicating what the first month of the time series is. 
+It can be from 1 to 12.}
 
-\item{moninf}{an integer indicating the month when to start the seasonal 
-means: 1 to 12.}
+\item{moninf}{An integer indicating the starting month of the seasonal mean. 
+It can be from 1 to 12.}
 
-\item{monsup}{an integer indicating the month when to stop the seasonal 
-means: 1 to 12.}
+\item{monsup}{An integer indicating the end month of the seasonal mean. It 
+can be from 1 to 12.}
+
+\item{method}{An R function to be applied for seasonal calculation. For
+example, 'sum' can be used for total precipitation. The default value is mean.}
+
+\item{na.rm}{A logical value indicating whether to remove NA values along 
+'time_dim' when calculating climatology (TRUE) or return NA if there is NA 
+along 'time_dim' (FALSE). The default value is TRUE.}
+
+\item{ncores}{An integer indicating the number of cores to use for parallel 
+computation. The default value is NULL.}
 }
 \value{
-Array with the same dimensions as var except along the posdim 
- dimension whose length corresponds to the number of seasons. Partial 
- seasons are not accounted for.
+An array with the same dimensions as data except along the 'time_dim' 
+ dimension, of which the length changes to the number of seasons.
 }
 \description{
-Computes seasonal means on timeseries organized in a array of any number of 
-dimensions up to 10 dimensions where the time dimension is one of those 10 
-dimensions.
+Compute the seasonal mean (or other methods) on monthly time series along
+one dimension of a named multi-dimensional arrays. Partial season is not 
+accounted.
 }
 \examples{
-# Load sample data as in Load() example:
-example(Load)
-leadtimes_dimension <- 4
-initial_month <- 11
-mean_start_month <- 12
-mean_stop_month <- 2
-season_means_mod <- Season(sampleData$mod, leadtimes_dimension, initial_month,
-                          mean_start_month, mean_stop_month)
-season_means_obs <- Season(sampleData$obs, leadtimes_dimension, initial_month,
-                          mean_start_month, mean_stop_month)
- \donttest{
-PlotAno(season_means_mod, season_means_obs, startDates, 
-       toptitle = paste('winter (DJF) temperatures'), ytitle = c('K'), 
-       legends = 'ERSST', biglab = FALSE, fileout = 'tos_season_means.eps')
- }
-}
-\author{
-History:\cr
-0.1  -  2011-03  (V. Guemas, \email{virginie.guemas@ic3.cat})  -  Original code\cr
-1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens@ic3.cat})  -  Formatting to CRAN
+dat <- 1 : (12 * 5 * 2 * 3 * 2)
+dim(dat) <- c(dat = 1, memb = 3, time = 12 * 5, lon = 2, lat = 2) 
+res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
+dat <- 1 : (12 * 2 * 3)
+dim(dat) <- c(dat = 2, time = 12, memb = 3)
+res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
+dat <- 1 : (24 * 2 * 3)
+dim(dat) <- c(dat = 2, time = 24, memb = 3)
+res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
+dat[c(1, 20, 50)] <- NA
+res1 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = FALSE)
+res2 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = TRUE)
 }
-\keyword{datagen}
 
diff --git a/tests/testthat/test-Season.R b/tests/testthat/test-Season.R
new file mode 100644
index 00000000..0f1cba62
--- /dev/null
+++ b/tests/testthat/test-Season.R
@@ -0,0 +1,122 @@
+context("s2dverification::Season tests")
+
+##############################################
+  # dat1
+  set.seed(1)
+  data1 <- array(rnorm(144*3), dim = c(member = 2, sdate = 12*3, ftime = 2, lon = 3))
+
+  # dat2
+  data2 <- data1
+  set.seed(2)
+  na <- floor(runif(30, min = 1, max = 144*3))
+  data2[na] <- NA
+
+##############################################
+test_that("1. Input checks", {
+
+  expect_error(
+  Season(c()),
+  "Parameter 'data' cannot be NULL."
+  )
+  expect_error(
+    Season(c(NA, NA)),
+    "Parameter 'data' must be a numeric array."
+  )
+  expect_error(
+    Season(list(a = array(rnorm(50), dim = c(dat = 5, sdate = 10)), b = c(1:4))),
+    "Parameter 'data' must be a numeric array."
+  )
+  expect_error(
+    Season(array(1:10, dim = c(2, 5))),
+    "Parameter 'data' must have dimension names."
+  )
+  expect_error(
+    Season(dat1, time_dim = 2),
+    "Parameter 'time_dim' must be a character string."
+  )
+  expect_error(
+    Season(dat1, time_dim = 'a'),
+    "Parameter 'time_dim' is not found in 'data' dimension."
+  )
+  expect_error(
+    Season(dat1, monini = 0, moninf = 1, monsup = 2),
+    "Parameter 'monini' must be a positive integer between 1 and 12."
+  )
+  expect_error(
+    Season(dat1, monini = 1, moninf = 'jan', monsup = 2),
+    "Parameter 'moninf' must be a positive integer between 1 and 12."
+  )
+  expect_error(
+    Season(dat1, monini = 1, moninf = 1, monsup = 'Jan'),
+    "Parameter 'monsup' must be a positive integer between 1 and 12."
+  )
+  expect_error(
+    Season(dat1, monini = 1, moninf = 1, monsup = 2, method = 'mean'),
+    "Parameter 'method' should be an existing R function, e.g., mean or sum."
+  )
+  expect_error(
+    Season(dat1, monini = 1, moninf = 1, monsup = 2, na.rm = na.omit),
+  "Parameter 'na.rm' must be one logical value."
+  )
+  expect_error(
+    Season(dat1, monini = 1, moninf = 1, monsup = 2, ncores = T),
+    "Parameter 'ncores' must be a positive integer."
+  )
+
+})
+
+##############################################
+test_that("2. Output checks: dat1", {
+
+  expect_equal(
+    dim(Season(data1, monini = 1, moninf = 1, monsup = 2)),
+    c(sdate = 3, member = 2, ftime = 2, lon = 3)
+  )
+  expect_equal(
+    dim(Season(data1, time_dim = 'lon', monini = 1, moninf = 1, monsup = 2)),
+    c(lon = 1, member = 2, sdate = 36, ftime = 2)
+  )
+  expect_equal(
+    dim(Season(data1, monini = 10, moninf = 12, monsup = 2)),
+    c(sdate = 3, member = 2, ftime = 2, lon = 3)
+  )
+  expect_equal(
+    summary(Season(data1, monini = 10, moninf = 12, monsup = 2))[3],
+    c(Median = 0.007925),
+    tolerance = 0.0001
+  )
+  expect_equal(
+    summary(Season(data1, monini = 10, moninf = 2, monsup = 5, method = sum))[3],
+    c(Median = 0.2732),
+    tolerance = 0.0001
+  )
+
+})
+
+##############################################
+test_that("3. Output checks: dat2", {
+
+  expect_equal(
+    summary(Season(data2, monini = 10, moninf = 12, monsup = 2))[3],
+    c(Median = -0.01987),
+    tolerance = 0.0001
+  )
+  expect_equal(
+    summary(Season(data2, monini = 10, moninf = 12, monsup = 2, na.rm = F))[3],
+    c(Median = 0.06207),
+    tolerance = 0.0001
+  )
+  res <- Season(data2, monini = 10, moninf = 12, monsup = 2, na.rm = F)
+  expect_equal(
+    length(res[which(is.na(as.vector(res)))]),
+    10
+  )
+  res <- Season(data2, monini = 10, moninf = 12, monsup = 2)
+  expect_equal(
+    length(res[which(is.na(as.vector(res)))]),
+    0
+  )
+})
+
+##############################################
+
-- 
GitLab


From 2581b87125ac677d2be8673fdec8d6e1f96af71f Mon Sep 17 00:00:00 2001
From: aho <an.ho@bsc.es>
Date: Thu, 30 Jan 2020 16:30:55 +0100
Subject: [PATCH 2/2] Correct Season() examples and unit tests.

---
 R/Season.R                   | 22 ++++++++++------------
 man/Season.Rd                | 22 ++++++++++------------
 tests/testthat/test-Season.R | 24 ++++++++++++------------
 3 files changed, 32 insertions(+), 36 deletions(-)

diff --git a/R/Season.R b/R/Season.R
index 22b3578c..5ba97869 100644
--- a/R/Season.R
+++ b/R/Season.R
@@ -26,18 +26,16 @@
 #'
 #'@import multiApply
 #'@examples
-#'dat <- 1 : (12 * 5 * 2 * 3 * 2)
-#'dim(dat) <- c(dat = 1, memb = 3, time = 12 * 5, lon = 2, lat = 2) 
-#'res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
-#'dat <- 1 : (12 * 2 * 3)
-#'dim(dat) <- c(dat = 2, time = 12, memb = 3)
-#'res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
-#'dat <- 1 : (24 * 2 * 3)
-#'dim(dat) <- c(dat = 2, time = 24, memb = 3)
-#'res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
-#'dat[c(1, 20, 50)] <- NA
-#'res1 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = FALSE)
-#'res2 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = TRUE)
+#'set.seed(1)
+#'dat1 <- array(rnorm(144*3), dim = c(member = 2, sdate = 12*3, ftime = 2, lon = 3))
+#'res <- Season(data = dat1, monini = 1, moninf = 1, monsup = 2)
+#'res <- Season(data = dat1, monini = 10, moninf = 12, monsup = 2)
+#'dat2 <- dat1
+#'set.seed(2)
+#'na <- floor(runif(30, min = 1, max = 144*3))
+#'dat2[na] <- NA
+#'res <- Season(data = dat2, monini = 3, moninf = 1, monsup = 2)
+#'res <- Season(data = dat2, monini = 3, moninf = 1, monsup = 2, na.rm = FALSE)
 #'@import multiApply
 #'@export
 Season <- function(data, time_dim = 'sdate', monini, moninf, monsup, 
diff --git a/man/Season.Rd b/man/Season.Rd
index f1e74d6a..fad6f22c 100644
--- a/man/Season.Rd
+++ b/man/Season.Rd
@@ -42,17 +42,15 @@ one dimension of a named multi-dimensional arrays. Partial season is not
 accounted.
 }
 \examples{
-dat <- 1 : (12 * 5 * 2 * 3 * 2)
-dim(dat) <- c(dat = 1, memb = 3, time = 12 * 5, lon = 2, lat = 2) 
-res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
-dat <- 1 : (12 * 2 * 3)
-dim(dat) <- c(dat = 2, time = 12, memb = 3)
-res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
-dat <- 1 : (24 * 2 * 3)
-dim(dat) <- c(dat = 2, time = 24, memb = 3)
-res <- Season(data = dat, monini = 1, moninf = 1, monsup = 2)
-dat[c(1, 20, 50)] <- NA
-res1 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = FALSE)
-res2 <- Season(data = dat, monini = 1, moninf = 1, monsup = 2, na.rm = TRUE)
+set.seed(1)
+dat1 <- array(rnorm(144*3), dim = c(member = 2, sdate = 12*3, ftime = 2, lon = 3))
+res <- Season(data = dat1, monini = 1, moninf = 1, monsup = 2)
+res <- Season(data = dat1, monini = 10, moninf = 12, monsup = 2)
+dat2 <- dat1
+set.seed(2)
+na <- floor(runif(30, min = 1, max = 144*3))
+dat2[na] <- NA
+res <- Season(data = dat2, monini = 3, moninf = 1, monsup = 2)
+res <- Season(data = dat2, monini = 3, moninf = 1, monsup = 2, na.rm = FALSE)
 }
 
diff --git a/tests/testthat/test-Season.R b/tests/testthat/test-Season.R
index 0f1cba62..b01b242b 100644
--- a/tests/testthat/test-Season.R
+++ b/tests/testthat/test-Season.R
@@ -3,13 +3,13 @@ context("s2dverification::Season tests")
 ##############################################
   # dat1
   set.seed(1)
-  data1 <- array(rnorm(144*3), dim = c(member = 2, sdate = 12*3, ftime = 2, lon = 3))
+  dat1 <- array(rnorm(144*3), dim = c(member = 2, sdate = 12*3, ftime = 2, lon = 3))
 
   # dat2
-  data2 <- data1
+  dat2 <- dat1
   set.seed(2)
   na <- floor(runif(30, min = 1, max = 144*3))
-  data2[na] <- NA
+  dat2[na] <- NA
 
 ##############################################
 test_that("1. Input checks", {
@@ -69,24 +69,24 @@ test_that("1. Input checks", {
 test_that("2. Output checks: dat1", {
 
   expect_equal(
-    dim(Season(data1, monini = 1, moninf = 1, monsup = 2)),
+    dim(Season(dat1, monini = 1, moninf = 1, monsup = 2)),
     c(sdate = 3, member = 2, ftime = 2, lon = 3)
   )
   expect_equal(
-    dim(Season(data1, time_dim = 'lon', monini = 1, moninf = 1, monsup = 2)),
+    dim(Season(dat1, time_dim = 'lon', monini = 1, moninf = 1, monsup = 2)),
     c(lon = 1, member = 2, sdate = 36, ftime = 2)
   )
   expect_equal(
-    dim(Season(data1, monini = 10, moninf = 12, monsup = 2)),
+    dim(Season(dat1, monini = 10, moninf = 12, monsup = 2)),
     c(sdate = 3, member = 2, ftime = 2, lon = 3)
   )
   expect_equal(
-    summary(Season(data1, monini = 10, moninf = 12, monsup = 2))[3],
+    summary(Season(dat1, monini = 10, moninf = 12, monsup = 2))[3],
     c(Median = 0.007925),
     tolerance = 0.0001
   )
   expect_equal(
-    summary(Season(data1, monini = 10, moninf = 2, monsup = 5, method = sum))[3],
+    summary(Season(dat1, monini = 10, moninf = 2, monsup = 5, method = sum))[3],
     c(Median = 0.2732),
     tolerance = 0.0001
   )
@@ -97,21 +97,21 @@ test_that("2. Output checks: dat1", {
 test_that("3. Output checks: dat2", {
 
   expect_equal(
-    summary(Season(data2, monini = 10, moninf = 12, monsup = 2))[3],
+    summary(Season(dat2, monini = 10, moninf = 12, monsup = 2))[3],
     c(Median = -0.01987),
     tolerance = 0.0001
   )
   expect_equal(
-    summary(Season(data2, monini = 10, moninf = 12, monsup = 2, na.rm = F))[3],
+    summary(Season(dat2, monini = 10, moninf = 12, monsup = 2, na.rm = F))[3],
     c(Median = 0.06207),
     tolerance = 0.0001
   )
-  res <- Season(data2, monini = 10, moninf = 12, monsup = 2, na.rm = F)
+  res <- Season(dat2, monini = 10, moninf = 12, monsup = 2, na.rm = F)
   expect_equal(
     length(res[which(is.na(as.vector(res)))]),
     10
   )
-  res <- Season(data2, monini = 10, moninf = 12, monsup = 2)
+  res <- Season(dat2, monini = 10, moninf = 12, monsup = 2)
   expect_equal(
     length(res[which(is.na(as.vector(res)))]),
     0
-- 
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