Export position_name

NAMESPACE

@@ -22,6 +22,7 @@ export(follow_up2)
 export(inspect)
 export(optimum_batches)
 export(optimum_subset)
+export(position_name)
 export(qcSubset)
 export(replicates)
 export(sizes_batches)

NEWS.md

@@ -10,8 +10,12 @@
 
 * Now it is possible to remove full rows or columns from `spatial()`: like `remove_positions = "A"` (#52).
 
+* Fix a bug in `spatial()` that in some cases assigned multiple samples to the same position (#51).
+
 * Spatial indexes are returned in row, column order: A1, A2, A3, ... A10, B1,. 
 
+* Function `position_name()` is now exported to facilitate generating designs. 
+
 # experDesign 0.3.0
 
 * Fixed a bug in `spatial()` where multiple samples could be assigned to the 

R/evaluate_category.R

@@ -79,7 +79,8 @@ evaluate_independence <- function(i, pheno) {
 #' @param pheno Data.frame with the variables of each sample, one row one sample.
 #' @param omit Character vector with the names of the columns to omit.
 #' @param na.omit Check the effects of missing values too.
-#' @return A logical value indicating if everything is alright (TRUE) or not (FALSE).
+#' @return A logical value indicating if everything is alright (`TRUE` or not (`FALSE`).
+#' @seealso [valid_followup()].
 #' @export
 #' @examples
 #' rdata <- expand.grid(sex = c("M", "F"), class = c("lower", "median", "high"))

R/follow_up.R

@@ -16,7 +16,7 @@
 #' data(survey, package = "MASS")
 #' survey1 <- survey[1:118, ]
 #' survey2 <- survey[119:nrow(survey), ]
-#' fu <- follow_up(survey1, survey2, size_subset = 50, iterations = 10)
+#' folu <- follow_up(survey1, survey2, size_subset = 50, iterations = 10)
 follow_up <- function(original, follow_up, size_subset, omit = NULL,
                       old_new = "batch", iterations = 500) {
   stopifnot(is.character(old_new) & length(old_new) == 1)

R/utils.R

@@ -68,7 +68,21 @@ translate_index <- function(index,
   index
 }
 
+
+#' Create position names for a grid.
+#'
+#' @param rows Names of the rows.
+#' @param columns Names of the columns.
+#'
+#' @return A data.frame with the rows and columns and the resulting name row+column.
+#' The name column is a factor for easier sorting in row, column order.
+#' @export
+#' @examples
+#' position_name(c("A", "B"), 1:2)
 position_name <- function(rows, columns) {
+  if (length(intersect(rows, columns)) >= 1) {
+    stop("rows and columns shouldn't share names.")
+  }
   positions <- expand.grid(rows, columns, stringsAsFactors = FALSE)
   colnames(positions)[1:2] <- c("row", "column")
   positions <- positions[order(positions$row, positions$column), ]

README.Rmd

@@ -26,15 +26,17 @@ knitr::opts_chunk$set(
 
 <!-- badges: end -->
 
-The goal of experDesign is to help you manage your samples before an experiment but after they are collected.
-For example, checking for common problems in the data, and help reduce or even prevent batch bias before performing an experiment, or measure once it is already done
+The goal of experDesign is to help you distribute your samples before an experiment but after they are collected. 
+For example, checking for common problems in the data, and reducing or even preventing batch bias before performing an experiment, or measuring it once the experiment is performed.
 It provides four main functions:
 
 * `check_data()`: Check if there are any problems with the data.
 * `design()`: Randomize the samples according to their variables.
 * `replicates()`: Selects some samples for replicates and randomizes the samples (highly recommended).
 * `spatial()`: Randomize the samples on a spatial grid.
 
+There are other helpers. 
+
 ## Installation
 
 To install the latest version on [CRAN](https://CRAN.R-project.org/package=experDesign) use:

README.md

@@ -22,18 +22,20 @@ developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.re
 
 <!-- badges: end -->
 
-The goal of experDesign is to help you manage your samples before an
+The goal of experDesign is to help you distribute your samples before an
 experiment but after they are collected. For example, checking for
-common problems in the data, and help reduce or even prevent batch bias
-before performing an experiment, or measure once it is already done It
-provides four main functions:
+common problems in the data, and reducing or even preventing batch bias
+before performing an experiment, or measuring it once the experiment is
+performed. It provides four main functions:
 
 - `check_data()`: Check if there are any problems with the data.
 - `design()`: Randomize the samples according to their variables.
 - `replicates()`: Selects some samples for replicates and randomizes the
   samples (highly recommended).
 - `spatial()`: Randomize the samples on a spatial grid.
 
+There are other helpers.
+
 ## Installation
 
 To install the latest version on
@@ -118,6 +120,9 @@ combination with the original according to multiple statistics.
 omit <- c("Wr.Hnd", "NW.Hnd", "Fold", "Pulse", "Clap", "Exer", "Height", "M.I")
 (keep <- colnames(survey)[!colnames(survey) %in% omit])
 #> [1] "Sex"   "W.Hnd" "Smoke" "Age"
+```
+
+``` r
 head(survey[, keep])
 #>      Sex W.Hnd Smoke    Age
 #> 1 Female Right Never 18.250
@@ -126,12 +131,18 @@ head(survey[, keep])
 #> 4   Male Right Never 20.333
 #> 5   Male Right Never 23.667
 #> 6 Female Right Never 21.000
+```
+
+``` r
 
 # Set a seed for reproducibility
 set.seed(87732135)
 # Looking for groups at most of 70 samples.
 index <- design(pheno = survey, size_subset = 70, omit = omit, iterations = 100)
 #> Warning: There might be some problems with the data use check_data().
+```
+
+``` r
 index
 #> $SubSet1
 #>  [1]   3   9  10  14  16  21  23  24  25  30  44  46  56  57  59  62  63  68  69
@@ -164,6 +175,9 @@ a colleague with:
 ``` r
 head(batch_names(index))
 #> [1] "SubSet3" "SubSet3" "SubSet1" "SubSet4" "SubSet2" "SubSet2"
+```
+
+``` r
 # Or via inspect() to keep it in a matrix format:
 head(inspect(index, survey[, keep]))
 #>      Sex W.Hnd Smoke    Age   batch
@@ -203,7 +217,9 @@ Two packages allow to distribute the samples on batches:
 
 If you are still designing the experiment and do not have collected any
 data [DeclareDesign](https://cran.r-project.org/package=DeclareDesign)
-might be relevant for you.
+might be relevant for you. But specially the
+[randomizr](https://cran.r-project.org/package=randomizr) packages which
+makes common forms of random assignment and sampling.
 
 Question in
 [Bioinformatics.SE](https://bioinformatics.stackexchange.com/q/4765/48)

_pkgdown.yml

@@ -53,6 +53,7 @@ reference:
     - valid_followup
   - title: "Other"
   - contents:
+    - position_name
     - create_subset
     - compare_index
     - entropy

cran-comments.md

@@ -1,2 +1,2 @@
-This updates adds some functions and fixes a bug found by a user.
+This updates adds some functions and fixes a bug.
 Checks passed without notes locally in some other machines there was a note about examples above 5s. 

tests/testthat/test-spatial.R

@@ -65,4 +65,13 @@ test_that("Removing columns works", {
   expect_lte(length(index2), 9*12)
   expect_true(all(names(index2) %in% position_name(rows = LETTERS[1:9], 1:12)$name))
   expect_false(any(table(batch_names(index), batch_names(index2)) > 1))
+})
+
+test_that("position_name works", {
+  expect_error(position_name(1:2, 1:2))
+  pn <- position_name(LETTERS[1:2], 1:2)
+  expect_s3_class(pn, "data.frame")
+  expect_equal(pn$row, rep(LETTERS[1:2], each = 2))
+  expect_equal(pn$column, rep(1:2, length.out = 4))
+  expect_equal(pn$name, as.factor(paste0(rep(LETTERS[1:2], each = 2), rep(1:2, length.out = 4))))
 })