matsbyname (version 0.6.11)

create_rowvec_byname: Create row vectors from data

Description

This function takes data in the .dat and creates row vectors.

Usage

create_rowvec_byname(
  .dat,
  dimnames = NA,
  rowname = NA,
  matrix_class = c("matrix", "Matrix")
)

Value

A row vector, a list of row vectors, or a data frame column of row vectors, depending on the values of .dat and class.

Arguments

.dat

Data to be converted to row vectors.

dimnames

The dimension names to be used for creating the row vector, in a list format, or as a data frame column containing a list of the dimension names to be used for each observation.

rowname

The name of the row of the row vector.

matrix_class

One of "matrix" or "Matrix". "matrix" creates a base::matrix object with the matrix() function. "Matrix" creates a Matrix::Matrix object using the matsbyname::Matrix() function. This could be a sparse matrix. Default is "matrix".

Details

The row and column names in the resulting row vector are taken from rowname and the names of .dat. If set, dimnames overrides rowname and the names of .dat.

Row types and column types are taken from the row type and column type attributes of .dat.

This function is a "byname" function that can accept a single number, a vector, a list, or a data frame in .dat.

Examples

# Works with single numbers
create_rowvec_byname(c(c1 = 1) %>% setrowtype("rt") %>% setcoltype("ct"), rowname = "r1")
# Works with vectors
create_rowvec_byname(c(c1 = 1, c2 = 2), rowname = "r1")
# Works with a list
create_rowvec_byname(list(c(c1 = 1, c2 = 2), c(C1 = 3, C2 = 4, C3 = 5)), 
                     rowname = list("r1", "R1"))
# Works in a tibble, too.
# (Must be a tibble, not a data frame, so that names are preserved.)
dat <- list(c(c1 = 1),
            c(C1 = 2, C2 = 3), 
            c(c1 = 1, c2 = 2, c3 = 3, c4 = 4, c5 = 5, c6 = 6))
rnms <- list("r1", "R1", "r1")
df1 <- tibble::tibble(dat, rnms)
df1
df1 <- df1 %>%
  dplyr::mutate(
    rowvec_col = create_rowvec_byname(dat, rowname = rnms)
  )
df1$rowvec_col[[1]]
df1$rowvec_col[[2]]
df1$rowvec_col[[3]]