Compare ⋅ llrs/experDesign

#' Given the index and the data of the samples append the batch assignment
#' @param i List of indices of samples per batch
#' @param pheno Data.frame with the sample information.
#' @param omit Name of the columns of the `pheno` that will be omitted
#' @param omit Name of the columns of the `pheno` that will be omitted.
#' @param index_name Column name of the index of the resulting data.frame.
#' @return The data.frame with a new column batch with the name of the batch the sample goes to.
#' @export
#' @examples

@@ -13,8 +14,11 @@

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#'                 iterations = 10)
#' batches <- inspect(index, survey[, columns])
#' head(batches)
inspect <- function(i, pheno, omit = NULL) {
inspect <- function(i, pheno, omit = NULL, index_name = "batch") {
  batch <- batch_names(i)
  i <- unlist(i, FALSE, FALSE)
  i <- sort(i)
  pheno <- pheno[i, ]

  # Omit columns
  if (!is.null(omit)) {

@@ -23,7 +27,9 @@

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    pheno_o <- pheno
  }

  cbind(pheno_o, batch)
  out <- cbind(pheno_o, batch)
  colnames(out)[ncol(out)] <- index_name
  out
}



@@ -20,10 +20,17 @@

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#' index
design <- function(pheno, size_subset, omit = NULL, iterations = 500,
                   name = "SubSet") {
  stopifnot(is.numeric(size_subset) && is.finite(size_subset))
  stopifnot(length(dim(pheno)) == 2)
  stopifnot(is.numeric(iterations) && is.finite(iterations))
  stopifnot(is.character(name))
  opt <- Inf

  # Calculate batches
  size_data <- nrow(pheno)
  if (size_subset >= size_data) {
    stop("All the data can be done in one batch.", call. = FALSE)
  }
  batches <- optimum_batches(size_data, size_subset)

  if (!valid_sizes(size_data, size_subset, batches)) {

@@ -86,9 +93,14 @@

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#' head(index)
replicates <- function(pheno, size_subset, controls, omit = NULL,
                       iterations = 500){
  stopifnot(is.numeric(size_subset))
  stopifnot(is.numeric(controls))
  stopifnot(is.numeric(size_subset) && is.finite(size_subset))
  stopifnot(length(dim(pheno)) == 2)
  stopifnot(is.numeric(iterations) && is.finite(iterations))

  size_data <- nrow(pheno)
  if (size_subset >= size_data) {
    stop("All the data can be done in one batch.", call. = FALSE)
  }
  if (size_subset < controls) {
    stop("The controls are technical controls for the batches.\n\t",
         "They cannot be above the number of samples per batch.", call. = FALSE)

@@ -19,6 +19,9 @@

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spatial <- function(index, pheno, omit = NULL, remove_positions = NULL, rows = LETTERS[1:5],
         columns = 1:10, iterations = 500) {

  stopifnot(length(dim(pheno)) == 2)
  stopifnot(is.numeric(iterations) && is.finite(iterations))

  nrow <- length(rows)
  ncol <- length(columns)


@@ -33,6 +36,7 @@

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         "\n\tPlease check the rows and columns or how you created the index.",
         call. = FALSE)
  }

  plate <- matrix(nrow = nrow, ncol = ncol, dimnames = list(rows, columns))
  positions <- position_name(rows, columns)
  if (any(!remove_positions %in% positions$name)) {

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Files		•	•	•	Coverage
QC.R	ø	ø	ø	ø	90.70%
designer.R	+10	+8	ø	+2	^-1.43% 85.42%
entropy.R	ø	ø	ø	ø	100.00%
evaluate.R	ø	ø	ø	ø	97.96%
evaluate_category.R	ø	ø	ø	ø	100.00%
evaluate_num.R	ø	ø	ø	ø	100.00%
indexing.R	ø	ø	ø	ø	82.14%
optimum.R	ø	ø	ø	ø	86.67%
reporting.R	+5	+5	ø	ø	^+4.46% 85.71%
spatial.R	+2	+2	ø	ø	^0.82% 81.25%
utils.R	ø	ø	ø	ø	83.78%
Folder Totals (11 files)	379	338	0	41	89.18%
Project Totals (11 files)	379	338	0	41	89.18%

23	27		pheno_o <- pheno
24	28		}
25	29
26		-	cbind(pheno_o, batch)
	30	+	out <- cbind(pheno_o, batch)
	31	+	colnames(out)[ncol(out)] <- index_name
	32	+	out
27	33		}
28	34
29	35

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Compare `a328d3d ... +18 ... 330fd39`

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20 Commits

3	3		#' Given the index and the data of the samples append the batch assignment
4	4		#' @param i List of indices of samples per batch
5	5		#' @param pheno Data.frame with the sample information.
6		-	#' @param omit Name of the columns of the `pheno` that will be omitted
	6	+	#' @param omit Name of the columns of the `pheno` that will be omitted.
	7	+	#' @param index_name Column name of the index of the resulting data.frame.
7	8		#' @return The data.frame with a new column batch with the name of the batch the sample goes to.
8	9		#' @export
9	10		#' @examples

13	14		#' iterations = 10)
14	15		#' batches <- inspect(index, survey[, columns])
15	16		#' head(batches)
16		-	inspect <- function(i, pheno, omit = NULL) {
	17	+	inspect <- function(i, pheno, omit = NULL, index_name = "batch") {
17	18		batch <- batch_names(i)
	19	+	i <- unlist(i, FALSE, FALSE)
	20	+	i <- sort(i)
	21	+	pheno <- pheno[i, ]
18	22
19	23		# Omit columns
20	24		if (!is.null(omit)) {

20	20		#' index
21	21		design <- function(pheno, size_subset, omit = NULL, iterations = 500,
22	22		name = "SubSet") {
	23	+	stopifnot(is.numeric(size_subset) && is.finite(size_subset))
	24	+	stopifnot(length(dim(pheno)) == 2)
	25	+	stopifnot(is.numeric(iterations) && is.finite(iterations))
	26	+	stopifnot(is.character(name))
23	27		opt <- Inf
24	28
25	29		# Calculate batches
26	30		size_data <- nrow(pheno)
	31	+	if (size_subset >= size_data) {
	32	+	stop("All the data can be done in one batch.", call. = FALSE)
	33	+	}
27	34		batches <- optimum_batches(size_data, size_subset)
28	35
29	36		if (!valid_sizes(size_data, size_subset, batches)) {

86	93		#' head(index)
87	94		replicates <- function(pheno, size_subset, controls, omit = NULL,
88	95		iterations = 500){
89		-	stopifnot(is.numeric(size_subset))
90		-	stopifnot(is.numeric(controls))
	96	+	stopifnot(is.numeric(size_subset) && is.finite(size_subset))
	97	+	stopifnot(length(dim(pheno)) == 2)
	98	+	stopifnot(is.numeric(iterations) && is.finite(iterations))
91	99
	100	+	size_data <- nrow(pheno)
	101	+	if (size_subset >= size_data) {
	102	+	stop("All the data can be done in one batch.", call. = FALSE)
	103	+	}
92	104		if (size_subset < controls) {
93	105		stop("The controls are technical controls for the batches.\n\t",
94	106		"They cannot be above the number of samples per batch.", call. = FALSE)

19	19		spatial <- function(index, pheno, omit = NULL, remove_positions = NULL, rows = LETTERS[1:5],
20	20		columns = 1:10, iterations = 500) {
21	21
	22	+	stopifnot(length(dim(pheno)) == 2)
	23	+	stopifnot(is.numeric(iterations) && is.finite(iterations))
	24	+
22	25		nrow <- length(rows)
23	26		ncol <- length(columns)
24	27

33	36		"\n\tPlease check the rows and columns or how you created the index.",
34	37		call. = FALSE)
35	38		}
	39	+
36	40		plate <- matrix(nrow = nrow, ncol = ncol, dimnames = list(rows, columns))
37	41		positions <- position_name(rows, columns)
38	42		if (any(!remove_positions %in% positions$name)) {

Compare a328d3d ... +18 ... 330fd39

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Compare `a328d3d ... +18 ... 330fd39`

Show failed CI and contexual commits `c`

20 Commits