diff --git a/R/Eno.R b/R/Eno.R
index 21899e737c5c0e7cf0aaaac07d789fc34b0b01f8..40ca54a372c98370ab38f82e335a3d7a59e17072 100644
--- a/R/Eno.R
+++ b/R/Eno.R
@@ -1,157 +1,108 @@
-#'Computes Effective Sample Size With Classical Method
+#'Compute effective sample size with classical method
 #'
-#'Computes the effective number of independent values along the posdim 
-#'dimension of a matrix.\cr
-#'This effective number of independent observations can be used in 
-#'statistical/inference tests.\cr
-#'Based on eno function from Caio Coelho from rclim.txt.
+#'Compute the number of effective samples along one dimension of an array. This
+#'effective number of independent observations can be used in statistical/inference 
+#'tests.\cr
+#'The calculation is based on eno function from Caio Coelho from rclim.txt.
 #'
-#'@param obs A numeric n-dimensional array with or without named dimensions.
-#'@param posdim A character or an integer indicating the dimension along 
-#'  which to compute the effective sample size.
-#'@param na.action Function to be called to handle missing values, can be 
-#'  na.pass or na.fail. Default: na.pass
-#'@param ncores The number of cores to use for parallel computation. Default: NULL
+#'@param data A numeric array with named dimensions.
+#'@param time_dim A function indicating the dimension along which to compute 
+#'  the effective sample size. The default value is 'sdate'.
+#'@param na.action A function. It can be na.pass (missing values are allowed) 
+#'  or na.fail (no missing values are allowed). See details in stats::acf(). 
+#'  The default value is na.pass.
+#'@param ncores An integer indicating the number of cores to use for parallel 
+#'  computation. The default value is NULL.
 #'
-#'@return An array with the same dimensions as obs except the posdim dimension.
+#'@return An array with the first dimension 'stats', which is the number of 
+#'  effective samples, and the following dimensions are same as parameter 'data'
+#'  except the time_dim dimension, which is removed after the computation.
 #'
 #'@keywords datagen
 #'@author History:\cr
-#'0.1  -  2011-05  (V. Guemas, \email{virginie.guemas at ic3.cat})  -  Original code\cr
-#'1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens at ic3.cat})  -  Formatting to R CRAN
-#'3.0  -  2019-08  (A. Ho, \email{an.ho@bsc.es})  -  Adopt multiApply
+#'0.1  -  2011-05  (V. Guemas, \email{virginie.guemas@ic3.cat})  -  Original code\cr
+#'1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens@ic3.cat})  -  Formatting to R CRAN
+#'3.0  -  2019-12  (A. Ho, \email{an.ho@bsc.es})  - Adopt multiApply feature
 #'
 #'@examples
-#'# See examples on Load() to understand the first lines in this example
-#'  \dontrun{
-#'data_path <- system.file('sample_data', package = 's2dverification')
-#'exp <- list(
-#'         name = 'experiment',
-#'         path = file.path(data_path, 'model/$EXP_NAME$/monthly_mean',
-#'                          '$VAR_NAME$_3hourly/$VAR_NAME$_$START_DATES$.nc')
-#'       )
-#'obs <- list(
-#'         name = 'observation',
-#'         path = file.path(data_path, 'observation/$OBS_NAME$/monthly_mean',
-#'                          '$VAR_NAME$/$VAR_NAME$_$YEAR$$MONTH$.nc')
-#'       )
-#'# Now we are ready to use Load().
-#'startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
-#'sampleData <- Load('tos', list(exp), list(obs), startDates,
-#'                   leadtimemin = 1, leadtimemax = 4, output = 'lonlat',
-#'                   latmin = 27, latmax = 48, lonmin = -12, lonmax = 40)
-#'  }
-#'  \dontshow{
-#'startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
-#'sampleData <- s2dverification:::.LoadSampleData('tos', c('experiment'), 
-#'                                                c('observation'), startDates,
-#'                                                output = 'lonlat', 
-#'                                                latmin = 27, latmax = 48, 
-#'                                                lonmin = -12, lonmax = 40) 
-#'  }
-#'sampleData$mod <- Season(sampleData$mod, 4, 11, 1, 12)
-#'eno <- Eno(sampleData$mod[1, 1, , 1, , ], 1)
-#'PlotEquiMap(eno, sampleData$lon, sampleData$lat)
+#'set.seed(1)
+#'data <- array(rnorm(800), dim = c(dataset = 1, member = 2, sdate = 4, 
+#'                                  ftime = 4, lat = 10, lon = 10))
+#'na <- floor(runif(40, min = 1, max = 800))
+#'data[na] <- NA
+#'res <- Eno(data)
 #'
 #'@importFrom stats acf na.pass na.fail
 #'@import multiApply
 #'@export
-Eno <- function(obs, posdim, na.action = na.pass, ncores = NULL) {
+Eno <- function(data, time_dim = 'sdate', na.action = na.pass, ncores = NULL) {
 
-  #Check params:
-
-  if (is.null(obs)) {
-    stop("Parameter 'obs' cannot be NULL.")
+  # Check inputs 
+  ## data
+  if (is.null(data)) {
+    stop("Parameter 'data' cannot be NULL.")
   }
-  if (!is.numeric(obs)) {
-    stop("Parameter 'obs' must be a numeric array.")
+  if (!is.numeric(data)) {
+    stop("Parameter 'data' must be a numeric array.")
   }
-
-  if (is.null(posdim)) {
-    stop("Parameter 'posdim' cannot be NULL.")
+  if (is.null(dim(data))) {  #is vector
+    dim(data) <- c(length(data))
+    names(dim(data)) <- time_dim
   }
-
-  if (!is.numeric(posdim) && !is.character(posdim)) {
-      stop("Parameter 'posdim' must be an positive integer or character.")
+  if(any(is.null(names(dim(data))))| any(nchar(names(dim(data))) == 0)) {
+    stop("Parameter 'data' must have dimension names.")
   }
-
-  if (is.numeric(posdim)) {
-    if (posdim <= 0 | posdim %% 1 != 0) {
-      stop("Parameter 'posdim' must be a positive integer or character.")
-    } else if (posdim > length(dim(obs))) {
-      stop("Parameter 'posdim' excesses the dimension length of parameter 'obs'.")
-    } else {  #posdim is okay for being integer. But change it to character.
-      if (!is.null(names(dim(obs)))) {
-        posdim <- names(dim(obs))[posdim]
-      } else {
-        names(dim(obs)) <- paste0("D", 1:length(dim(obs)))
-        posdim <- names(dim(obs))[posdim]
-      }
-    }
+  ## time_dim
+  if (!is.character(time_dim) | length(time_dim) > 1) {
+    stop("Parameter 'time_dim' must be a character string.")
   }
-
-  if (is.character(posdim)) {
-    if (is.null(names(dim(obs)))) {
-      stop(paste0("Parameter 'obs' doesn't have dimension names. ", 
-                  "Add names or specify parameter 'posdim' by number."))
-    } else if (!any(posdim %in% names(dim(obs)))) {
-      stop(paste0("Parameter 'posdim' does not match any dimension name of ",
-                  "parameter 'obs'."))
-    }
+  if (!time_dim %in% names(dim(data))) {
+    stop("Parameter 'time_dim' is not found in 'data' dimension.")
   }
-
-  if (as.character(substitute(na.action)) != c("na.pass") &&
+  ## na.action
+  if (as.character(substitute(na.action)) != c("na.pass") &
       as.character(substitute(na.action)) != c("na.fail")) {
-      stop("Parameter 'na.action' must be either 'na.pass' or 'na.fail'.")
+      stop("Parameter 'na.action' must be a function either na.pass or na.fail.")
   }
-
-  if(as.character(substitute(na.action))== c("na.fail") && any(is.na(obs))) {
-    stop(paste0("NA value in paratemter 'obs', which is not accepted when ",
-                "parameter 'na.action' = 'na.fail'."))
+  if(as.character(substitute(na.action))== c("na.fail") && any(is.na(data))) {
+    stop(paste0("Calculation fails because NA is found in paratemter 'data', ",
+                "which is not accepted when ",
+                "parameter 'na.action' = na.fail."))
   }
-
+  ## ncores
   if (!is.null(ncores)) {
-    if (!is.numeric(ncores)) {
-      stop("Parameter 'ncores' must be a positive integer.")
-    } else if (ncores <= 0 | ncores %% 1 != 0) {
+    if (!is.numeric(ncores) | ncores %% 1 != 0 | ncores < 0 |
+      length(ncores) > 1) {
       stop("Parameter 'ncores' must be a positive integer.")
     }
   }
 
-  #Calculation:
+  ###############################
+  # Calculate Eno
 
-  effnumobs <- Apply(data = list(obs),
-                     target_dims = posdim,
-                     fun = .Eno,
-                     na.action = na.action,
-                     ncores = ncores)$output1
+  eno <- Apply(data = list(data),
+               target_dims = time_dim,
+               output_dims = 'stats',
+               fun = .Eno,
+               na.action = na.action,
+               ncores = ncores)$output1
 
-  return(effnumobs)
+  return(eno)
 }
 
 .Eno <- function(x, na.action) {
-  # Checks:
-  if (!is.numeric(x)) {
-      stop("Parameter 'x' must be a numeric vector.")
-  }
-
-  if (length(sort(x)) > 1) {
-    n <- length(sort(x))
-#    if (n == 0) {
-#      n <- 1
-#  }
+  n <- length(sort(x))
+  if (n > 1) {
     a <- acf(x, lag.max = n - 1, plot = FALSE,
              na.action = na.action)$acf[2:n, 1, 1]
     s <- 0
     for (k in 1:(n - 1)) {
       s <- s + (((n - k) / n) * a[k])
     }
-
     eno <- min(n / (1 + (2 * s)), n)
-
   } else {
     eno <- NA
   }
-  eno
+  return(as.array(eno))
 }
 
diff --git a/man/Eno.Rd b/man/Eno.Rd
index b2a3123d81cd8727f783698b6c6b0f2d5e9dac66..e81832edd0454605ef014a0fc33131cd7cea6431 100644
--- a/man/Eno.Rd
+++ b/man/Eno.Rd
@@ -2,69 +2,49 @@
 % Please edit documentation in R/Eno.R
 \name{Eno}
 \alias{Eno}
-\title{Computes Effective Sample Size With Classical Method}
+\title{Compute effective sample size with classical method}
 \usage{
-Eno(obs, posdim, na.action = na.pass, ncores = NULL)
+Eno(data, time_dim = "sdate", na.action = na.pass, ncores = NULL)
 }
 \arguments{
-\item{obs}{A numeric n-dimensional array with or without named dimensions.}
+\item{data}{A numeric array with named dimensions.}
 
-\item{posdim}{A character or an integer indicating the dimension along 
-which to compute the effective sample size.}
+\item{time_dim}{A function indicating the dimension along which to compute 
+the effective sample size. The default value is 'sdate'.}
 
-\item{na.action}{Function to be called to handle missing values, can be 
-na.pass or na.fail. Default: na.pass}
+\item{na.action}{A function. It can be na.pass (missing values are allowed) 
+or na.fail (no missing values are allowed). See details in stats::acf(). 
+The default value is na.pass.}
 
-\item{ncores}{The number of cores to use for parallel computation. Default: NULL}
+\item{ncores}{An integer indicating the number of cores to use for parallel 
+computation. The default value is NULL.}
 }
 \value{
-An array with the same dimensions as obs except the posdim dimension.
+An array with the first dimension 'stats', which is the number of 
+ effective samples, and the following dimensions are same as parameter 'data'
+ except the time_dim dimension, which is removed after the computation.
 }
 \description{
-Computes the effective number of independent values along the posdim 
-dimension of a matrix.\cr
-This effective number of independent observations can be used in 
-statistical/inference tests.\cr
-Based on eno function from Caio Coelho from rclim.txt.
+Compute the number of effective samples along one dimension of an array. This
+effective number of independent observations can be used in statistical/inference 
+tests.\cr
+The calculation is based on eno function from Caio Coelho from rclim.txt.
 }
 \examples{
-# See examples on Load() to understand the first lines in this example
- \dontrun{
-data_path <- system.file('sample_data', package = 's2dverification')
-exp <- list(
-        name = 'experiment',
-        path = file.path(data_path, 'model/$EXP_NAME$/monthly_mean',
-                         '$VAR_NAME$_3hourly/$VAR_NAME$_$START_DATES$.nc')
-      )
-obs <- list(
-        name = 'observation',
-        path = file.path(data_path, 'observation/$OBS_NAME$/monthly_mean',
-                         '$VAR_NAME$/$VAR_NAME$_$YEAR$$MONTH$.nc')
-      )
-# Now we are ready to use Load().
-startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
-sampleData <- Load('tos', list(exp), list(obs), startDates,
-                  leadtimemin = 1, leadtimemax = 4, output = 'lonlat',
-                  latmin = 27, latmax = 48, lonmin = -12, lonmax = 40)
- }
- \dontshow{
-startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
-sampleData <- s2dverification:::.LoadSampleData('tos', c('experiment'), 
-                                               c('observation'), startDates,
-                                               output = 'lonlat', 
-                                               latmin = 27, latmax = 48, 
-                                               lonmin = -12, lonmax = 40) 
- }
-sampleData$mod <- Season(sampleData$mod, 4, 11, 1, 12)
-eno <- Eno(sampleData$mod[1, 1, , 1, , ], 1)
-PlotEquiMap(eno, sampleData$lon, sampleData$lat)
+set.seed(1)
+data <- array(rnorm(800), dim = c(dataset = 1, member = 2, sdate = 4, 
+                                 ftime = 4, lat = 10, lon = 10))
+na <- floor(runif(40, min = 1, max = 800))
+data[na] <- NA
+res <- Eno(data)
 
 }
 \author{
 History:\cr
-0.1  -  2011-05  (V. Guemas, \email{virginie.guemas at ic3.cat})  -  Original code\cr
-1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens at ic3.cat})  -  Formatting to R CRAN
-3.0  -  2019-08  (A. Ho, \email{an.ho@bsc.es})  -  Adopt multiApply
+0.1  -  2011-05  (V. Guemas, \email{virginie.guemas@ic3.cat})  -  Original code\cr
+1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens@ic3.cat})  -  Formatting to R CRAN
+3.0  -  2019-12  (A. Ho, \email{an.ho@bsc.es})  - Adopt multiApply feature
+
 }
 \keyword{datagen}
 
diff --git a/tests/testthat/test-Eno.R b/tests/testthat/test-Eno.R
index e8c7e6cd30605b4c602e9f3ba5ed67ce09b6fe6f..5c11dee97ca575b6eea472abab2b4974f4a0819e 100644
--- a/tests/testthat/test-Eno.R
+++ b/tests/testthat/test-Eno.R
@@ -1,102 +1,92 @@
-context("Generic tests")
-test_that("Sanity checks", {
+context("s2dverification::Eno tests")
 
-#error
-  expect_error(
-    Eno(NULL),
-    "Parameter 'obs' cannot be NULL."
-  )
+##############################################
+  set.seed(1)
+  dat1 <- array(rnorm(800), dim = c(dataset = 1, member = 2, sdate = 4, 
+                                    ftime = 4, lat = 10, lon = 10))
+  set.seed(1)
+  na <- floor(runif(40, min = 1, max = 800))
+  dat1[na] <- NA
 
-  expect_error(
-    Eno(c('a', 'b'), posdim = 1),
-    "Parameter 'obs' must be a numeric array."
-  )
 
-  expect_error(
-    Eno(1:10, c()),
-    "Parameter 'posdim' cannot be NULL."
-  )
+  dat2 <- array(c(-5, -7, -10:10, 12, 11, 7, 16), 
+                dim = c(date = 13, ftime = 2))
 
-  expect_error(
-    Eno(1:10, posdim = FALSE),
-    "Parameter 'posdim' must be an positive integer or character."
-  )
+##############################################
+test_that("1. Input checks", {
 
   expect_error(
-    Eno(1:10, posdim = -1),
-    "Parameter 'posdim' must be a positive integer or character."
+  Eno(c()),
+  "Parameter 'data' cannot be NULL."
   )
-
   expect_error(
-    Eno(1:10, posdim = 1.2),
-    "Parameter 'posdim' must be a positive integer or character."
+  Eno(data = 'a'),
+  "Parameter 'data' must be a numeric array."
   )
-
   expect_error(
-    Eno(array(1:10, dim = c(2, 5)), 3),
-    "Parameter 'posdim' excesses the dimension length of parameter 'obs'."
+  Eno(data = array(1:10, dim = c(2,5))),
+  "Parameter 'data' must have dimension names."
   )
-
-  dat <- array(1:10, dim = c(2, 5))
   expect_error(
-    Eno(dat, 'a'),
-    paste0("Parameter 'obs' doesn't have dimension names. ",
-           "Add names or specify parameter 'posdim' by number.")
+  Eno(data = 1:10, time_dim = 12),
+  "Parameter 'time_dim' must be a character string."
   )
-
-  names(dim(dat)) <- c('a', 'b')
   expect_error(
-    Eno(dat, 'c'),
-    paste0("Parameter 'posdim' does not match any dimension name of ",
-           "parameter 'obs'.")
+  Eno(data = array(1:10, dim = c(a = 2, b = 5))),
+  "Parameter 'time_dim' is not found in 'data' dimension."
   )
-
   expect_error(
-    Eno(dat, 'a', na.action = na.stop),
-    "Parameter 'na.action' must be either 'na.pass' or 'na.fail'."
+  Eno(data = array(1:10, dim = c(a = 2, sdate = 5)), na.action = na.rm),
+  "Parameter 'na.action' must be a function either na.pass or na.fail."
   )
-
-  dat[1] <- NA
   expect_error(
-    Eno(dat, 'a', na.action = na.fail),
-    paste0("NA value in paratemter 'obs', which is not accepted when ",
-           "parameter 'na.action' = 'na.fail'.")
+  Eno(data = c(NA,1:19), na.action = na.fail),
+  paste0("Calculation fails because NA is found in paratemter 'data', ",
+                "which is not accepted when ",
+                "parameter 'na.action' = na.fail.")
   )
-
   expect_error(
-    Eno(dat, 'a', ncores = FALSE),
-    "Parameter 'ncores' must be a positive integer."
+  Eno(data = array(1:10, dim = c(a = 2, sdate = 5)), ncores = 0.5),
+  "Parameter 'ncores' must be a positive integer."
   )
 
-  expect_error(
-    Eno(dat, 'a', ncores = 1.5),
-    "Parameter 'ncores' must be a positive integer."
-  )
+})
 
-#equal
-  dat <- array(1:10, dim = c(2, 5))
+##############################################
+test_that("2. Output checks: dat1", {
+  res <- Eno(dat1)
 
   expect_equal(
-    names(dim(Eno(dat, 1))),
-     c('D2')
+    dim(res),
+    dim(array(dim = c(stats = 1, dataset = 1, member = 2, ftime = 4, lat = 10, lon = 10)))
   )
 
-  names(dim(dat)) <- c('a', 'b')
   expect_equal(
-    Eno(dat, 1),
-     array(rep(2, 5), dim = c(b = 5))
+    length(res[which(is.na(res))]),
+    1
   )
 
-  dat[1] <- NA
   expect_equal(
-    Eno(dat, 2)[1],
-    4
+    length(res[which(res != 4)]),
+    37
   )
 
   expect_equal(
-    Eno(dat, 1)[1],
-    as.numeric(NA)
+    mean(res, na.rm = T),
+    2.768103,
+    tolerance = 0.0001
   )
 
 })
 
+##############################################
+
+test_that("3. Output checks: dat2", {
+
+  expect_equal(
+    Eno(dat2, time_dim = 'date'),
+    array(c(6.237689, 5.683186), dim = c(stats = 1, ftime = 2)),
+    tolerance = 0.0001
+  )
+
+})