matrixStats (version 0.53.1)

rowAlls: Checks if a value exists / does not exist in each row (column) of a matrix

Description

Checks if a value exists / does not exist in each row (column) of a matrix.

Usage

rowAlls(x, rows = NULL, cols = NULL, value = TRUE, na.rm = FALSE,
  dim. = dim(x), ...)
colAlls(x, rows = NULL, cols = NULL, value = TRUE, na.rm = FALSE,
  dim. = dim(x), ...)
allValue(x, idxs = NULL, value = TRUE, na.rm = FALSE, ...)
rowAnys(x, rows = NULL, cols = NULL, value = TRUE, na.rm = FALSE,
  dim. = dim(x), ...)
colAnys(x, rows = NULL, cols = NULL, value = TRUE, na.rm = FALSE,
  dim. = dim(x), ...)
anyValue(x, idxs = NULL, value = TRUE, na.rm = FALSE, ...)

Arguments

x

An NxK matrix or an N * K vector.

value

A value to search for.

na.rm

If TRUE, NAs are excluded first, otherwise not.

dim.

An integer vector of length two specifying the dimension of x, also when not a matrix.

...

Not used.

idxs, rows, cols

A vector indicating subset of elements (or rows and/or columns) to operate over. If NULL, no subsetting is done.

Value

rowAlls() (colAlls()) returns an logical vector of length N (K). Analogously for rowAnys() (rowAlls()).

Logical <code>value</code>

When value is logical, the result is as if the function is applied on as.logical(x). More specifically, if x is numeric, then all zeros are treates as FALSE, non-zero values as TRUE, and all missing values as NA.

Details

These functions takes either a matrix or a vector as input. If a vector, then argument dim. must be specified and fulfill prod(dim.) == length(x). The result will be identical to the results obtained when passing matrix(x, nrow = dim.[1L], ncol = dim.[2L]), but avoids having to temporarily create/allocate a matrix, if only such is needed only for these calculations.

See Also

rowCounts

Examples

# NOT RUN {
x <- matrix(FALSE, nrow = 10, ncol = 5)
x[3:7, c(2, 4)] <- TRUE
x[2:4, ] <- TRUE
x[, 1] <- TRUE
x[5, ] <- FALSE
x[, 5] <- FALSE
print(x)

print(rowCounts(x))       # 1 4 4 4 0 3 3 1 1 1
print(colCounts(x))       # 9 5 3 5 0

print(rowAnys(x))
print(which(rowAnys(x)))  # 1  2  3  4  6  7  8  9 10
print(colAnys(x))
print(which(colAnys(x)))  # 1 2 3 4
# }